One Year of Data Science @ Capgemini

This past week I celebrated my one year anniversary with Capgemini’s Advanced Insights and Analytics division as a Senior Data Scientist. I’ve worked on several engagements and POC’s, using a range of technologies to provide automated solutions for our clients. These technologies have included using Spark libraries (SparkR, PySpark), distributed computing platforms (Databricks, Snowflake), and multiple cloud services (Azure Data Factory, Google Cloud, Amazon SageMaker), all of which have been new learning opportunities to embrace.

Today, I want to share some non-technical insights I have had over the past year. I now find these to be essential for my success at Capgemini, as well as any future career I should hold. This advice is catered towards those entering the remote tech world, mainly when faced with a culture that encourages ownership of one’s own career and doesn’t hand an outline for them to follow.

Data Science is both wide and deep

“Data Scientist” is a challenging title in its obscurity. Data Scientists are often tasked with handling a wide range of responsibilities: business communicator, data engineer, business analyst, interviewer of subject matter experts, machine learning researcher… you get the idea. The job goes wide. This is in large part to the still relative newness of the role and an industry that is still changing at a rapid rate in its development and application of technology.

My focus when applying for this role, and the main aspect of why I have stayed, has been to get a wide absorption of the industry. At some point, Data Science tends to favor and encourage going deep into either a specific subject-matter, industry, and/or domain of machine learning. For example, marketing specialists tend to know quite a lot about their industry (e.g. A/B customer testing, retention and churn analytics) and not too much outside that industry (e.g. supply chain optimization). Other Data Scientists tend to focus on computer vision research work (deep) for a range of industries in manufacturing, fashion, life-sciences, etc. (wide).

When considering and identifying the roles and work you are interested in, it can be helpful to weigh this balance of wide and deep work in your decision-making process. Further, staffing plans for new projects that have a balance of people between these two extremes can prove successful.

Virtual Connections Matter

There is no breakroom to casually interact with your co-workers anymore. Socialization is only guaranteed to come from the interactions we encourage and initiate ourselves. While this makes focusing on work easier, not talking to co-workers can lead to self-isolation and negative feedback cycles that lead to feeling like you aren’t part of the bigger team and project.

In seriousness, connections matter, even virtually fostered ones. You need others on and off your team to advocate for you in meetings that you aren’t in, and the only way they will do so is if you make that connection feel relevant and meaningful through consistent positive interaction.

A simple practice is to set up bi-monthly / monthly reoccurring invites with co-workers that you want to continue interacting to make it easy and simple for casual interaction to occur, thus building rapport. “What if I get busy when the meeting comes around?” Just reschedule! It’s easier to change a date than to make on in the first place.

This is a practice that is most important to set and formalize with your manager. At Capgemini, I have a People Manager who is responsible for my career and staffing goals. It is imperative for my success that I continuously check-in with them on my goals and aspirations. They can also offer insight into what opportunities are available for different projects and promotions. These conversations are also a place for you to advocate for yourself and ask for what you need to succeed. You have no right to complain if you don’t ask.

No one will gift you with praise or their presence if you don’t prioritize and plan personal time in the first place!

Project Lifecycle

In tech consulting space, you tend to find yourself in projects at different stages of their lifecycle. Some still need to be designed, many are being maintained and iterated upon, and others are near their final scoped deliverable. Being thrown into this machine can be challenging! Communicating with your new team, asking detailed relevant questions, and requesting considerable knowledge transfer is key to success. This may seem obvious at first, but not doing so can lead to deeper challenges in your work down the road.

This is particularly true if you turn into too much of a “Yes” person and let work pile up that is not your responsibility while taking care of other’s work streams.

My main point here is to evaluate and direct your workflow as early as possible to avoid the big scary word: Burnout. The best time to avoid burnout is when you are not burnt-out. Crazy, I know. But evaluating how you are balancing work and avoiding taking too much on your plate is essential to long term success. As one of my coworkers puts it, while agile platforms like to break work into so called “sprints”, the project itself is a marathon and should be treated as such. Stability is the way to success, both for your career and the code you develop.

What happens if you are already burnt-out? This is often caused by either project scoping being done poorly OR feeling obligated to do more work than is expected of you. In a remote world it can be easy to feel like you aren’t doing enough work, and you should address why you feel the need to provide so many hours to a project. This is an important conversation to have with someone you trust in the workplace and evaluate solutions to scale back your output.

Doing more work than needed and expected will hurt your team in three big ways:

  1. The client and project managers will expect that this is a normal amount of work to expect, and thus will eventually burn you out and lose a valuable resource for the practice.
  2. Team members with a better sense of balancing work with other life obligations (family, kids, health, classwork) will be expected to rise to your level rather than bring you down, and thus challenge their work life balance and affect team morale and increase general attrition.
  3. In all honesty, in consulting you are hurting the firm’s bottom-line! Your additional work could be applied to an additional resource who could sustainably bill the client.

In my opinion, a good consulting motto to follow is this: “Under-promise, over-deliver, and always be delivering.”

Keep Learning!

As mentioned earlier, data science is an ever expanding and improving field of work and study. Thus, it is important to keep up with the general progress and trends present in the community.

There are a few productive ways to do this:

  1. Take advantage of free learning opportunities and credentials provided by your company. Many employers offer online learning platforms at a stiff discount, or even free! I was able to get my Databricks badge coursework and testing fully paid for by work. In addition, I am now getting my Google Cloud Platform engineer certification paid for as well.
  2. Talk and network with co-workers! At Capgemini, we have a wide array of talented DS with assorted backgrounds that lend to unique experiences and perspectives on the work we can and do provide our clients with.
  3. Find opportunities to learn in new, diverse ways as well. Leading technical interviews, participating in internal data science challenges, and assisting co-workers with pitch decks provides a nice range of exposure to ideas and concepts that might not be clear to you at first. As David Epstein talks about in their book Range, “breadth of training predicts breadth of transfer. That is, the more contexts in which something is learned, the more the learner creates abstract models, and the less they rely on any particular example. Learners become better at applying their knowledge to a situation they’ve never seen before, which is the essence of creativity.” 1

To reiterate, sustainability is key. Find what works for you to capture and retain information without trying to swallow the sea of info online.


Starting a career in the pandemic era online can be tough, but it doesn’t have to be. I hope to continue to share my thoughts on how to tackle the ever-changing landscape as I go forward in my professional life, both as a benchmark for myself and resource for others.

Footnotes + Citations

  1. Epstein, David J., 1980-, Range: Why Generalists Triumph in a Specialized World. New York: Riverhead Books, 2019. Epstein, David J. Range: Why Generalists Triumph in a Specialized World.