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MIT’s Leaders for Global Operations (LGO) Dual Degree Program

Leverage the tools you gain in our MBA/MS from the Sloan School of Management and School of Engineering at MIT to become an innovative business leader with the technical skills to implement complex operations, manufacturing, and data analytics solutions across industries.

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LGOs join an extensive and collaborative community with the next generation of engineering leaders to solve global problems that serve society.

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Upcoming Admissions Events

Mit lgo • virtual conversation with admissions, mit lgo • information session, recent blog posts, black history month 2024: ololade olaleye, lgo ’24.

What were you doing before LGO and why did you decide that LGO was the next step for you?

Prior to applying to LGO, I worked at an energy company where I held various roles in and collaborated across projects, engineering, risk management, benchmarking, supply chain, business transformation, operations, and commercial functions. Through these experiences spanning both technology and business functions, I realised that I enjoyed working at the intersection of the two domains and providing value to my organisation in both capacities. This realisation led me to the LGO program, which stands at the confluence of business and technology. I believed that LGO would offer me the opportunity to refine and expand upon the skills I had begun to cultivate, by providing a structured and comprehensive educational experience tailored to professionals at the intersection of these critical areas.

What is your favorite memory from your time at MIT?

I have many fond memories from my time at MIT, but a few stand out as particular favourites. One of the most fun memories was dancing the night away at an Africa Business Club event. Spending cherished time with club members and friends created an incredible sense of community. Also, I greatly enjoyed the LGO Domestic Plant Trek, which provided the opportunity to travel across the US to visit and learn about several manufacturing companies, all expenses paid. From an academic perspective, some of my most enriching experiences came from impactful classes and working with my supportive advisors and supervisors on my internship project.

How have you engaged with affinity groups or diversity initiatives while at MIT?

Within the LGO community, I participated in committees such as the LGO Allyship committee, which I helped set up the summer potluck. In the broader MIT community, I serve as a Vice President of the Africa Business Club(ABC). I am also Chair of Operations for the MIT Africa Innovate Conference(AIC) 2024 and was a member of the planning committee for AIC 2023. In addition, I am a member of the Black Business Students Association(BBSA) and the MIT Black graduate student association. I am also a member of Sloan Women in Management, where I have mentored incoming first year Sloan women. I also participate in several other clubs, volunteer at conferences and mentor first year and undergraduate students.  

Do you have any advice for prospective students thinking about applying?

“Just do it!”, with adequate preparation. Do not hesitate to reach out to people and ask for help. The LGO program office, students and alumni are also great resources to utilise.

MIT LGO Summer Core Reflections: Alix Carson, LGO ’25

My name is Alix Carson and I am an LGO ’25 in the Mechanical Engineering Cohort. Before coming to LGO, I was a mechanical design engineer in the aerospace industry. I designed LiDAR cameras for military applications and propulsion systems for lower-earth orbit cargo modules. I came to LGO to pursue an interest in advanced manufacturing and operations. At LGO, I am the co-chair of the LGO New Student Recruiting Committee and am engaged with the Sloan Women in Management (SWIM).

Regarding classmates:

The LGO 2025 class has exceeded my expectations. Our class has a very tight bond that formed over our summer core and is full of extremely smart, but humble people.LGO attracts self-selected social nerds who want to pursue an MBA while growing their technical expertise. I have learned so much from my LGO peers. The backgrounds and experiences are vast in our class. We have everything from management consultants to engineers that designed campgrounds to army special forces veterans. It makes the classroom discussions very rich since we have so many people from various industries, backgrounds, and nationalities in one cohesive cohort. Outside of the classroom, our cohort invests time to socialize and support each other. One of our LGOs recently had a baby, so we threw a baby shower and organized a meal train to help support their family. We have gone to rugby games to support one of our peers who plays semi-professional rugby. We even threw a wedding party mid-summer because two LGOs in our cohort got married! I have been most surprised by the strength of our women in LGO cohort. We have a large representation of women in our cohort, and I am very thankful to have such a tight WLGO community.

Regarding classes:

The LGO summer core picks up from day one. We spend ten weeks taking courses in leadership, data science, linear optimization, and operations management. While the workload is intense, it is so rewarding to have classes under your belt before starting the Sloan core with the rest of the MBA class. The summer core is also a bonding experience for the class as we spend all day together and get broken into core teams that you work with to complete all your assignments. My LGO core team was the highlight of my summer. I met some of my closest friends, and we all felt so bittersweet to have the summer end and start our Sloan journey. One of my core team members perfectly summarized our experience this summer by saying that he had never been part of a team that so wholly accepted and embraced his authentic, quirky self. I couldn’t agree more. The summer core was a great way to get adjusted to being back in school and bonding with my cohort before starting the fall semester.

Regarding expectations:

The LGO summer core exceeded my expectations. Every alumnus you speak to will say that LGO summer core is one of the best parts of the two-year program. While going through it, it is hard to see how special it is when focused on homework deadlines and group projects. But looking back on it, I realize how much our class not only capitalized on learning together in the classroom but maximized our enjoyment of the summer. We had day trips to explore Massachusetts beaches, long bike rides to Walden Pond, and group sails on the Charles to name a few activities. We all liked each other so much that spending all week in a classroom together wasn’t enough, so then we’d spend all weekend together. It went by so fast, and I would go back and do it all over again.

Regarding everything else:

I am so thankful I chose to come to LGO. It is great to be back in the classroom learning and challenging myself with new, interesting topics from Competitive Strategy to Artificial Intelligence uses for social impact. LGOs have the unique opportunity to integrate into the MIT community in three ways: as an LGO, an engineering grad student, and an MBA student. The communities that LGO spans enriches your time on campus as you can dive into such a wide range of communities on campus from Sloan specific clubs to engineering sponsored seminars and cross-campus clubs, like MIT Driver less. Each LGO takes a unique approach to their experience which helps everyone get a little taste of what’s going on around campus. I am constantly inspired by what my peers are getting involved with around campus. As I am about to wrap up my Sloan fall core semester, I am in disbelief that I have been on campus for almost six months. I can’t wait to choose my spring semester schedule and go on the domestic plant trek with my class in January, but don’t want part of our class to leave so soon for February start internships! The program has flown by but it is very exciting to look forward to the events to come.

Veterans Spotlight: Andrew Dugan, LGO ’25

Introduction

My name is Andrew Dugan, LGO 25 (MBA /MechE).  I spent ten years on active duty in the Army before coming to LGO.  I spent the first few years of my career as an Infantry officer before transitioning to Special Forces.  I am joined at LGO with my wife, Leigh, and daughters, Harper (2) and Lilliana (16 days).  I did my undergrad at the United States Military Academy, where I studied mechanical engineering. My goal at LGO is to make a career pivot from the military into sustainability.

Transitioning from the Military to LGO

Leaving the Army after ten years was not initially on my family’s radar.  Everything changed once we had our first daughter, howe ver.  My third deployment was my first with a daughter, and after missing her first Christmas, birthday, and steps, we decided it was time for a change.  I was weary of applying to schools because I hadn’t been a student in nearly a decade and was concerned about losing a steady paycheck.  It was through conversations with Adam Barber (LGO 23 / Veteran), that I was convinced that applying to LGO was the right move for me and my career.  This was my first introduction to the LGO community, and I was beyond impressed.

My biggest concern before the summer semester started was that I was going to be the oldest person in the room, and also the least academically qualified.  Fortunately, I was only the second oldest.  Although the academics were challenging this summer, this is where I discovered the value of LGO. Through the rigorous summer, my peers and I bonded and helped each other out.  We became a tight knit team, and all supported each other.  It was a level of camaraderie I did not expect to form post military, and it has so far been my favorite part of this experience.

The fall core has been an excellent experience so far.  Mine has been much different than most, because my wife just recently gave birth to our second daughter.  MIT has been unbelievably accommodating during this time.  From professors being flexible, to my peers bringing over food almost nightly as my family adjusted to our newest member.

Academically it has been rewarding as well.  On top of the Sloan core classes, I am taking a class on finance, AI/ML, and sustainability.  I have been able to craft my schedule to meet my interests.  At LGO, I get to take classes with some of the smartest people I have ever met.  Initially it was incredible intimidating to be in the same small group with people who I considered to be brilliant.  Over time though, I learned that I also belong here.

Leaving the Army was a tough decision, but ultimately, we are extremely happy with our decision to come to LGO.  From rewarding academics to an incredible community, it has been as advertised.  I am not your average LGO.  I am 33, have 2 kids, and have never once called myself an engineer.  Despite all of those things, I have been welcomed by all of my peers.

Advice to Veterans Applying

My biggest advice to veterans applying to LGO is to be confident in yourself and your abilities.  Every veteran has a unique story and has gone through experiences that most have not.  Learn how to tell that story and be confident in doing so.   For our entire military careers, we are taught to never take credit for anything, and always recognize the team over yourself.  During the application process, this has to change.  You need to find a way to quantify the impact that you had.

My other piece of advice is to reach out to current and past veterans of LGO.  I talked to probably every veteran who had gone through the program in the last 5 years with a family.  Everyone was more than willing to talk to me, and share with me their experiences.

The MIT LGO Review

Technology and Leadership in Operations

Machine Learning – Beyond the Hype

By MARIA EMILIA LOPEZ MARINO

Maria Emilia Lopez Marino (LGO ’19) was the recipient of the 2019 Best Thesis Award for her work in collaboration with Amgen, Inc., advised by MIT professors Roy Welsch and Philip Gschwend, which involved the development of a predictive framework using machine learning techniques to assess the impact of raw material variability on the performance of commercial biologic manufacturing processes. The resulting model demonstrated an average of 89 % accuracy predicting product quality attributes and other critical process performance variables, and it was implemented as an internal Amgen web-tool [4]. 

The implementation of machine learning techniques in industry is still relatively nascent, and as a result many companies encounter unanticipated challenges when first exploring their potential applications. In this article, I identify three key challenges of developing and implementing a predictive model that emerged over the course of my project at Amgen and discuss how they can be avoided.

Earlier this year, LinkedIn co-founder Allen Blue reported that data science and machine learning-related jobs represent five of the top 15 fastest-growing jobs in America today [1]. This phenomenon is driven by computational advances that have enabled long-existing artificial intelligence (AI) techniques, as well as increased understanding of the value of automating processes in the private sector. Machine learning (ML), a branch of AI, has already begun revolutionizing the field of operations. Today, companies are using ML to predict when a manufacturing part will fail, to decide whether or not to treat a crop with a pesticide by analyzing visual data, and to improve customer experience in retail through the use of virtual assistants [2]. The growth of applied ML is also reflected in the LGO program’s activities: ML was the research focus of 10% of theses in 2018, 22% in 2019, and 25% in 2020 [3]. Addressing the implementation challenges described below can help companies that are starting to apply ML-based tools in their business better prepare for success.

TIP: Defining the Scope of a Machine Learning Project

Challenge 1: incorporating problem-specific input into the data preparation process .

Data extraction and clean-up is often one of the most time-consuming (and painful) steps of any analytics project, especially when dealing with “legacy” systems that were designed for now decades-old computational processes. One might assume that this task should fall to data scientists; however, a cross-functional approach that considers both ontology and feature engineering is necessary to develop a successful model. When I first began extracting data for the model, I spent countless hours scrubbing and curating it into a format that was compatible with the predictive algorithms. Afterward, I tested the data by running it through the model and—the results were disappointing. The model’s accuracy level was similar to the results one would achieve from randomly guessing. I realized that in the process of preparing the data, I had focused primarily on ontology engineering.

After talking with some of Amgen’s experts in cell culture processing, I discovered that my data set was missing features (process and material attributes) with greater predictive power. For example, instead of just using the daily record of a process variable as one of the key features, I could further transform the data, deriving relationships from original features, and include the integral value of the daily record, which turned out to be a better predictor judging from model performance metrics. Although good ontology engineering is critical for developing a data set for a predictive model, collaboration with domain experts enables the development of richer, more accurate models. In other words, you are then helping your algorithm focus on what your subject matter expert knows is important, based on mechanistic or first principle modeling.

Challenge 2: Spending too much effort (with diminishing returns) refining an overly sophisticated model

After the data has been prepared, you are ready to begin the real “machine learning”: training and evaluating the model. A key challenge of this stage is to strike the right balance between refining the model to achieve superior results and settling for a simpler model that meets the criteria for the specific application. I addressed this trade-off by defining a target quality measure for model performance up front and implementing ready-made ML algorithms from data science platforms [5]. We defined the bounds for model performance by implementing off-the-shelf methods which are known to perform well on a range of predictive model problems, such as random forests. We then aimed to find simpler models that achieved similar or improved performance. First, we implemented very simple models, such as linear regressions and simple regression trees, to achieve model convergence. We then increased the model complexity by looping around different algorithms, performing a search of the model that performed better according to our selected quality metric ( coefficient of determination or area under the ROC curve depending on the type of problem in hand: regression or classification). 

Although we could have further increased the complexity of the model by incorporating additional ML algorithms, such as neural networks, we recognized that it would not increase model performance radically and could possibly compromise interpretability. Another downside of developing an extremely sophisticated model is that it can be more difficult to generalize to other applications.

Challenge 3: Designing a user interface for your model that is suitable for non-experts

In the excitement of getting positive results from your model, it can be easy to forget to consider the most important factor for long-term success: the end user. In many cases, the end users of ML models will not be data scientists. As such, it is essential to develop a user-friendly interface for the model, as well as a guide for using the tool, while keeping the client’s original motivation for the project in mind. The end users for the model we developed for Amgen were manufacturing processes monitoring teams and upstream cell culture manufacturing teams, consisting of mostly engineers and technicians. Some of the teams had already started using ML tools in their daily routines, while others had little to no prior experience applying data science in their work. In addition to the interface design, running workshops with end users helped ensure the usability and sustainability of the tool.

In order to successfully develop a ML-based tool, it is important to take a cross-functional approach, use the simplest model possible, and ensure that the end-product is user-friendly. This list of challenges is not exhaustive, but they are likely to be encountered in any application of ML. By navigating them successfully, you can unlock the potential of predictive modeling to better achieve your business goals.

[1] What is driving the demand for data scientists?, Wharton, UPenn, March 8th 2019.

[2] Marr, Bernard, 27 Incredible Examples Of AI And Machine Learning In Practice, Forbes, April 30th 2018.

[3] LGO Program Office, September 8th 2019.

[4] María Emilia López Marino, Big Data Analysis Interrogating Raw Material Variability and the Impact on Process Performance, LGO Thesis, May 8th 2019.

[5] Scikit-Learn, https://scikit-learn.org

[6] Sekhar, Amit, What Is Feature Engineering for Machine Learning?, Medium, February 14th 2018.

[7] Descriptive, predictive, prescriptive: Transforming asset and facilities management with analytics, Watson IoT, IBM, December 2017.

About the Author

Trained as a Chemical Engineer in Argentina, Maria Emilia has served in roles varying from logistics engineer to manufacturing engineer and manager at large consumer goods firms, inlcuding Procter & Gamble and Johnson & Johnson. Maria Emilia graduated from the LGO program in 2019 and recently joined Amgen’s Operations Leadership Program.

Leaders for Global Operations (LGO) Fellows Program

Principal Investigator Patricia Eames

Project Website http://lgo.mit.edu/mba-dual-degree-program.html

The Leaders for Global Operations (LGO) program is an educational and research partnership among global operations companies and MIT’s School of Engineering and the MIT Sloan School of Management. Its objective is to discover, codify, teach, and otherwise disseminate guiding principles for world-class manufacturing and operations.

The LGO program combines graduate education in engineering and management for those with two or more years of work experience who aspire to leadership positions in manufacturing or operations companies. A required 6.5-month internship provides opportunity to complete a research project on site at one of LGO’s partner companies. The internship leads to a dual-degree thesis, culminating in two master’s degrees -- an S.M. in management or an M.B.A., and an S.M. in engineering. The program is offered jointly through the MIT Sloan School of Management and the School of Engineering master’s programs in:

(*) Aeronautics and Astronautics (*) Biological Engineering (*) Chemical Engineering (*) Civil and Environmental Engineering (*) Electrical Engineering and Computer Science (*) Engineering Systems (*) Materials Science and Engineering (*) Mechanical Engineering

LGO's curriculum is designed to teach students an appreciation for continuous, incremental improvement as well as for groundbreaking innovation - and it provides the tools to accomplish both. Through class work, research, and opportunities to lead and learn by doing, LGO gives students a solid background in critical areas of manufacturing, including manufacturing processes, design and development, operations management, information technology, teamwork, leadership, change management, and systems thinking.

The LGO program provides many opportunities for students to learn about and practice leadership skills through carefully planned activities. Starting with The Universe Within and a course during the first summer, activities focus on continuous leadership discovery, reflection, interaction, and development. LGOs meet and discuss critical manufacturing challenges with people from a wide variety of perspectives, including partner company executives, other LGO alumni and plant floor workers.

Students take the lead in managing the Proseminars, plant treks, and committees such as Marketing and Admissions, Internships, Strategy & Vision, and LGO Alumni.

In the News

From LGO to PhD

Many students in MIT’s Leaders for Global Operations (LGO) program return to the workplace primed to tackle complex operational problems. But sometimes their research sparks deep scholarly interest, and they bring their LGO toolkit into an academic career instead.

MIT-LGO-to-PHD-01-press_0.jpg

That was the case for Jimmy Smith SM ’18, MBA ’18, who’s currently pursuing a PhD in computational mathematics at Stanford University. He specializes in machine learning models for sequence data.

Smith was ready to accelerate his career as a drilling engineer at BP Exploration Alaska, so he enrolled in the LGO program for experience in engineering management. There, he worked with Goodyear to develop machine learning algorithms to automate a tire-inspection process. He realized that he wanted to explore machine learning even more deeply. Instead of polishing his resume, he began preparing applications to PhD programs, all with the support of MIT mentors.

“LGO opened up the world for me. Getting exposure to so many students and faculty with different interests helped me to gain a better understanding of what I wanted out of my career,” he says.

Smith’s advisor, mechanical engineering professor David Hardt, praises LGO’s natural link between industry and academia. Having worked closely with Smith in his manufacturing statistics class and applauding his curiosity, he wrote Smith a glowing recommendation letter for Stanford.

With LGO, “You get a holistic perspective,” Hardt says. “While LGO students are not research students — they’re professionals doing a project in an industry that ends up as a thesis — Jimmy was asking the probing questions that you’d want in a PhD student.” 

While the LGO program isn’t a traditional training ground for PhD candidates, it’s a highly useful one, Smith says. The work he pursued, initially for a professional edge, ended up blossoming into an intellectual passion.

“LGO exposed me to the machine-learning, AI-type things that I’m interested in now. The master’s thesis component gave me an opportunity to do meaningful research, and working with faculty advisors at MIT gave me a better sense of what doing research full time as a PhD student would be like,” he explains. “I realized it was something I was really interested in and excited about.” 

Smith’s revelatory experience isn’t unusual for LGO students, says MIT LGO executive director Thomas Roemer.

“Students come to us because they want to change direction in life in some way. And some, while at MIT, discover how much they love learning and how much they love being at a university. They may get inspired by professors and say, ‘Hey, this is what I would like to do: become a professor myself,’” he says.

Like Smith, Audrey Bazerghi SM ’20, MBA ’20, a former management consultant, didn’t enter MIT with the desire to pursue a PhD. Before enrolling, she worked for Oliver Wyman, focusing on the manufacturing, transportation, and energy space. She was at a career crossroads and wanted to refine her math and modeling skills. She graduated with a newfound passion for research.

“I focused a lot of my coursework at MIT on supply chain and on questions regarding procurement or logistics that I ran into in my time as a consultant. I discovered through my LGO internship and thesis requirements that I really enjoyed research,” she recalls. “LGO allowed me to discover that I liked it enough to do it full time.”

Now she’s a second-year PhD student at Northwestern University’s Kellogg School of Management, focusing on operations management. Bazerghi hopes to teach master's of business administration students, ideally helping them to apply cutting-edge operations knowledge to their respective industries. It’s a logical extension of the hands-on education she received at MIT.

“That’s what LGO really is about: How do we organize work so that it serves its purpose? And I think it’s more relevant than ever that people understand that,” says Deishin Lee ’90, SM ’92.

To that end, she’s now an associate professor of operations management and sustainability at Ivey Business School in London, Ontario. The LGO program — at the time called Leaders for Manufacturing — imparted an appreciation for the connection between academics and practicality, which she now shares with her students. In fact, Lee worked at Motorola for seven years before obtaining her PhD. It was a useful strategy. The real-world experience she got on the job helps her teach organizational pain points from a lived perspective.

“The problem is that sometimes students don’t have an appreciation for the problems organizations have. It’s difficult to evaluate the effectiveness of various solutions, if you don’t understand the problem — that comes from an understanding of how organizations work,” she says. “LGO was enormously helpful because we saw so many different organizations, and we had so many managers come and talk to us.”

While the vast majority of LGO alumni reenter the workforce, Roemer hopes that prospective students enter MIT with an open mind.

“[The LGO program] is a life-changing opportunity that will really have a huge impact on their future lives, not so much in terms of careers — of course they’ll have great careers — but in terms of how they look at the world,” he says. “And that transition, in those two years, may go in all sorts of directions.”

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9 Keys to Successfully Break Into VC

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By  Lindsey Nicholson , MBA Career Advisor

Are you excited about VC and want to recruit, but not sure where to get started? VC is a small and competitive industry, and recruiting can be challenging, even for the most qualified candidates. Unlike some other career paths that have a clear route and structure, VC can feel like a vine-ridden jungle, with no clear direction. Recruiting in VC is highly self-driven, requires extensive networking, and takes grit and perseverance. Whether you are just starting your VC job search, or you have been searching for a while and feel like you’re not getting traction, the recommendations below will help you move forward or adjust course in the right direction! 

• Build a Strong Understanding of the Industry: Before you start thinking about your job search, start learning about the venture capital industry. Learn about VC investments, the structure of VC firms, what VCs do, the skills they use, and the terminology of the industry. Reading blog posts, listening to podcasts, signing up for newsletters, and talking with people who know/understand the space are a few great ways to do this. This foundational understanding is key to being able to do Step 2 well. Resources : How Venture Capitalists Make Decisions | Introducing the VC Business | VC Glossary of Terms
• Clarify Your Why: Once you learn more about VC, it is essential to clarify your why . Why do you want to pursue a career in VC? What specifically about the industry excites you? What kind of firm do you want to be at (what stage, sector, etc), and what kind of role do you want? Running a VC job search requires much more specificity than simply, “I want to work in VC.” Given that it is such a competitive industry, it’s particularly important to be able to communicate to others in the industry why you are excited about VC and how your unique background and experience align, so you need to identify where and how you can best contribute. Resources: Questions to Ask Yourself  
• Identify Your Targets: Once you clarify why you are interested in VC, start building a list of the companies and VCs you want to connect with. Be strategic (don’t reach out to any and every VC around) but also be open-minded. Go beyond the big names and look for firms with an investment thesis that you believe in and that aligns with your background, experience, and interests. Before reaching out, make sure they are a potential fit: does what you want align with the firm’s work? Resources: PitchBook | VC Mapping  
• Build Relationships: Building relationships in VC is the number one thing you can do to help your job search! It is a highly relationship-driven industry, and the relationships that you build will both help you in your search and in your career as a venture capitalist. Be prepared for every conversation: do your research on the firm, their investment thesis/portfolio, and whom you are talking with. Treat every conversation like an interview ; you never know when an opportunity will arise from a conversation, and the company is evaluating your potential candidacy even in less formal conversations. Add value whenever you can,and stay in touch/top of mind. Track who you networked with and when using Airtable , a Google Doc , etc. Students often underestimate how long it can take to build a relationship with a VC through networking, and underestimate how many conversations they may need to have. Resources: The Art of Networking in VC
• Connect with Founders: A significant part of what VC Associates do is source investments, so building your network of founders and connecting with startups is essential to success in VC. If you aren’t already immersed in the entrepreneurial ecosystem, now is the time to start. Engage with the rich entrepreneurial community at MIT and beyond; attend conferences and events for startups; find and connect with seed-stage companies that excite you. Plus, a great way to add value as you network with VCs is to send them a startup you’ve discovered that you think would be a great fit for their firm. Resources : PitchBook | Crunchbase
• Identify Your Gaps/Refine Your Skills: As you start talking to people in the industry and learning more about the core experiences and competencies VCs need, start thinking about any gaps you may have on your resume. In addition to industry knowledge, VCs need associates who can analyze market trends, financial statements, and business models. Strong quantitative skills including financial modeling are important, as well as the ability to conduct due diligence on potential investments and assess the viability of startups. Having experience in the startup ecosystem, either as a founder or operator, is also important. In addition to hard skills, soft skills are key; to be successful, venture capitalists need excellent networking and communications skills, and an ability to handle ambiguity. Be honest with yourself and ask, where are my gaps and where do I need to build my skill set? Aside from my skills, am I personally cut out for the VC space? Identify key areas for growth and map out how you will fill these gaps in the coming months/year. Tip : Paste your work experience from your resume into Copilot and ask it to identify any gaps on your resume for a VC role.
• Build Industry Expertise / Have an Opinion: Often students entering the VC industry are eager to be a generalist investor. While a deep and open curiosity will benefit your VC career, being too broad in your approach may not benefit your job search. Seasoned VCs typically advise those entering the industry to pick a sector and specialize. 1 What areas excite you? What is your unique background and what unique industry knowledge do you already bring? Develop an opinion and have a perspective on what’s happening in the startup ecosystem within a particular sector. This will make you memorable as you connect with others in the industry, give you something to talk about in interviews and set you up for success as you start your VC career.
• Gain Hands-on Experience: The best way to set yourself up for success in VC is to gain experience in VC. VCs usually hire people who have had previous experience in the industry and have developed pattern recognition to identify promising startups. There are an increasing number of part-time fellowships and programs for students to learn and gain hands-on experience in the industry. These can be paid or unpaid and can range in time commitment and responsibilities. Before diving in, make sure you do your research and talk to alumni of the program to get a sense of what you’ll be learning/doing. Resource : List of VC Fellowships
• Start Acting Like a VC: Lastly, a common piece of advice we hear is to “act like a VC before you are a VC”. Do the industry research, conduct market analysis, identify startups that excite you, and bring VCs deals that match with their investment thesis. Resource : How to Get Hired as a Venture Associate

VC is a competitive industry and VC is not a safe or guaranteed route (we always recommend having a Plan B in your back pocket). It takes patience, grit, determination, and an ability to navigate ambiguity. These characteristics of the job search itself also reflect the life of a venture capitalist, and if you find yourself burning out through the search itself, reflect on whether it’s the right career path for you. However, for those who are up for the challenge, we hope this guidance helps you trod the unbeaten path.

1 Three Pieces of Advice to New Investors | by Jeremy Liew | Lightspeed Venture Partners | Medium