I DoorDash about 5 months in the past. That is my first time beginning at a brand new firm as a Knowledge Science Supervisor. DoorDash strikes quick, expectations are excessive, and the area context is deep, which makes onboarding difficult. Nonetheless, it has additionally been one of many fastest-growing durations of my profession.
The primary three months at any new job are basically a constructing part — constructing connections, area understanding, and information data — and a clean onboarding units the inspiration for later success. Due to this fact, on this article, I’ll share what mattered most at first months and my guidelines for any information science onboarding.
I. Construct Connections
Earlier than the rest, let me begin with constructing connections. After I was in school, I pictured information scientists as folks spending all day lengthy heads-down writing code and constructing fashions. Nonetheless, as I turned extra senior, I spotted that information scientists make actual impacts by embedding themselves deeply within the enterprise, utilizing information to establish alternatives, and driving enterprise choices. That is very true right now with tighter DS headcount and AI automating primary coding and evaluation workflows.
Due to this fact, constructing connections and incomes a seat on the desk must be a prime precedence throughout onboarding. This contains:
- Frequent onboarding periods along with your supervisor and onboarding buddy. These are the individuals who greatest perceive your future scope, expectations, and priorities. In my case, my supervisor was my onboarding buddy, and we met nearly each day throughout the first two weeks. I all the time got here with a ready record of questions I encountered throughout onboarding.
- Arrange meet-and-greet calls with cross-functional companions. Right here is the agenda I normally observe in these calls:
- 1. Private introductions
- 2. Their focus space and prime priorities
- 3. How my workforce can greatest help them
- 4. Any onboarding recommendation or “issues I ought to know”
- I particularly just like the final query because it persistently supplies nice insights. 5 years in the past, once I onboarded at Brex, I requested the identical query and summarised the responses into classes right here. The perfect I obtained this time is “Don’t be afraid to ask dumb questions. Play the new-hire card as a lot as attainable within the first three months.”
- For these key companions, arrange weekly/bi-weekly 1:1s and get your self added to recurring undertaking conferences. You might not contribute a lot at first, however simply listening in and amassing the context and questions is useful.
- In case you are onboarding as a supervisor like me, it’s best to begin speaking to your direct experiences early. Throughout onboarding, I purpose to study three issues from my direct experiences: 1. Their initiatives and challenges, 2. Their expectation of me as a supervisor, 3. Their profession targets. The primary helps me ramp up on the world. The latter two are vital for establishing belief and a collaborative working relationship early on.
II. Construct Area Context
Knowledge scientists succeed after they perceive the enterprise effectively sufficient to affect choices — not simply analyze outcomes. Due to this fact, one other precedence throughout onboarding is to construct your area data. Widespread methods embrace speaking to folks, studying docs, looking Slack, and asking a variety of questions.
I normally begin with conversations to establish key enterprise context and initiatives. Then I dig into related docs in Google Drive or Confluence, and browse Slack messages in undertaking channels. I additionally compile the questions after studying the docs, and ask them in 1:1s.
Nonetheless, one problem I bumped into is digging into the rabbit gap of docs. Every doc results in extra paperwork with quite a few unfamiliar metrics, acronym names, and initiatives. That is particularly difficult as a supervisor — if every of your workforce members has 3 initiatives, then 5 folks means 15 initiatives to catch up. At one level, my browser’s “To Learn” tab group had over 30 tabs open.
Fortunately, AI instruments are right here to rescue. Whereas studying all of the docs one after the other is useful to get an in depth understanding, AI instruments are nice to supply a holistic view and join the dots. For instance,
- At DoorDash, Glean has entry to inner docs and Slack. I usually chat with Glean, asking questions like “How is GOV calculated?”, “Present a abstract of the undertaking X, together with the objective, timeline, findings, and conclusion.” It hyperlinks to the doc sources, so I can nonetheless dive deeper rapidly if wanted.
- One other instrument I attempted is NotebookLM. I shared the docs on a selected subject with it, and requested it to generate summaries and thoughts maps for me to gather my ideas in a extra organized method. It could actually additionally create podcasts, that are typically extra digestible than studying docs.
- Different AI instruments like ChatGPT may also connect with inner docs and serve an identical function.
III. Construct Knowledge Information
Constructing information data is as essential as constructing area data for information scientists. As a front-line supervisor, I maintain myself to a easy normal: I ought to be capable to do hands-on information work effectively sufficient to supply sensible, credible steerage to my workforce.
Here’s what helped me ramp up rapidly:
- Arrange tech stack in week one: I like to recommend establishing the tech stack and developer surroundings early. Why? Entry points, permissions, and peculiar surroundings issues all the time take longer than anticipated. The sooner you’ve got every thing arrange, the earlier you can begin enjoying with the info.
- Make full use of AI-assisted information instruments: Each tech firm is integrating AI into its information workflows. For instance, at DoorDash, we have now Cursor linked to Snowflake with inner information data and context to generate SQL queries and evaluation grounded in our information. Although the generated queries are usually not but 100% correct, the tables, joins, and previous queries it factors me to function glorious beginning factors. It gained’t exchange your technical judgment, but it surely dramatically reduces the time to first perception.
- Perceive key metrics and their relationships: Knowledge data not solely means with the ability to entry and question the info, however perceive the enterprise from a knowledge lens. I normally begin with weekly enterprise evaluations to seek out the core metrics and their development. That is additionally an effective way to contextualize the metrics and have an thought of what “regular” appears to be like like. I’ve discovered this extremely useful when gut-checking analyses and experiment outcomes later.
- Get your arms soiled: Nothing enforces your information understanding greater than doing a little hands-on work. onboarding program normally features a mini starter undertaking. Whilst a supervisor, I did some IC work throughout my onboarding, together with alternative sizing for the planning cycle, designing and analyzing a number of experiments, and diagnosing and forecasting metrics motion. These initiatives accelerated my studying way over passive studying.
IV. Begin Small and Contribute Early
Whereas onboarding is primarily about studying, I strongly advocate beginning small and contributing early. Early contributions sign possession and construct belief — usually sooner than ready for a “excellent” undertaking. Listed below are some concrete methods:
- Enhance the onboarding documentation: As you undergo the onboarding doc, you’ll run into random technical points, discover damaged hyperlinks, or discover outdated directions. Not simply overcoming them your self, however enhancing the onboarding doc is an effective way to indicate that you’re a workforce participant and need to make onboarding higher for future hires.
- Construct documentation: No firm has excellent documentation — from my very own expertise and chatting with my associates, most information groups face the problem of outdated or lacking documentation. As you might be onboarding and never busy with initiatives but, it’s the excellent time to assist fill in these gaps. For instance, I constructed a undertaking listing for my workforce to centralize previous and ongoing initiatives with key findings and clear factors of contact. I additionally created a set of metrics heuristics, summarising the causal relationship between completely different metrics we discovered from previous experiments and analyses. Word that each one these paperwork additionally change into invaluable context for AI brokers, bettering the standard and relevance of AI-generated outputs.
- Recommend course of enhancements: Each information workforce operates in a different way, with execs and cons. Becoming a member of a brand new workforce means you carry a contemporary perspective on workforce processes and may spot alternatives to enhance effectivity. Considerate strategies based mostly in your previous expertise are tremendous invaluable.
In my view, a profitable onboarding goals to determine cross-functional alignment, enterprise fluency, and information instinct.
Right here is my onboarding guidelines:
- Week 1–2: Foundations
– Meet key enterprise companions
– Get your self added to core cross-functional conferences
– Perceive workforce focus and priorities at a high-level
– Arrange tech stack, entry, and permissions
– Write your first line of code
– Learn documentation and ask questions - Week 2–6: Get your arms soiled
– Deep dive into workforce OKR and generally used information tables
– Deep dive into your focus space (extra docs and questions)
– Full a starter undertaking end-to-end
– Make early contributions: Replace outdated information, construct one piece of documentation, or recommend one course of enchancment, and so on. - Week 6–12: Possession
– Be capable of communicate up in cross-functional conferences and supply your data-informed perspective
– Construct belief because the “go-to” individual to your area
Onboarding appears to be like completely different throughout firms, roles, and seniority ranges. However the ideas keep constant. In case you’re beginning a brand new function quickly, I hope this guidelines helps you ramp up with extra readability and confidence.
