AI is the new electricity. Millions of AI engineers are needed to transform industries with AI, particularly in the realm of GenAI, and we’re building an education platform to train them. With a mission to grow and connect the global AI community, DeepLearning.AI is an education technology company that is empowering the global workforce to build an AI-powered future through world-class education, hands-on training, and a collaborative community. We’re a small tech company with serious credentials, exciting marketing challenges, and wonderful teammates.
We have a lot of data - across our learning platform, Stripe, HubSpot, PostHog, customer.io, website analytics, NPS surveys, and more - and strong engineering capacity. We know the broad shape of the questions we want to answer, spanning topics such as growth, retention, monetization, and product engagement. We’re now looking to build a solid analytical layer - someone to translate our business questions into the right metrics, dig into the data to actually answer them, and - as a byproduct - leave behind a clean, durable data foundation that gets stronger with each cycle.
We are looking for a short-term consultant to work directly with our COO and business units leaders on the above, be able to generate value in week one and build the architecture iteratively against real questions.
What you'll do:
First week: lightweight orientation on existing pipelines, warehouse, and Metabase setup. Stakeholder conversations with leaders across Product, Marketing and other teams. Align on the first ~10 most important metrics and questions to tackle.
2nd week onwards: work through that first batch - define the metrics precisely, perform EDA to answer the questions (including the why behind them and any obviously related questions), ship dashboards or analyses that stakeholders can use, and as you go, build out the data models, naming conventions, and pipeline pieces needed to support those metrics durably. Then move to another batch of ~10, then another, and another, …
You'll be partnering and working closely with our COO and our data team from day one - not handing off specs for the team to build but rather doing real hands-on collaborative work (SQL, dbt, Python, whatever the right tool is).
The model we have in mind:
With each cycle, we’ll uncover real answers to real business questions, and gain incremental, well-designed foundations that the next cycle can build on.
Deliverables:
Answered business questions with the reasoning behind them, in whatever format makes them usable.
Working data models, transformations, and naming conventions that support those answers durably and that the next cycle can build on (as a byproduct of answering business questions iteratively).
A lightweight running, living view of what's been built and what's coming next - only as needed for us to always know where we are.
We need quick value generated, not beautiful summary decks and long documents.
Who we're looking for:
3+ years of experience as a data scientist with a strong analytical instinct, ability to translate ambiguous business questions into well-defined metrics and the judgment to know which questions are actually worth answering.
AI-native builder, leveraging latest tools and AI-assisted coding to dramatically accelerate productivity. Hands-on with SQL and Python, and comfortable doing real EDA.
Enough engineering chops to collaborate with our data eng team and make sound calls about data modeling, naming, and transformation layer design.
Comfortable asking questions, making suggestions and pushing back in executive meetings.
A practical bias - natural tendency to close projects and answer questions iteratively as opposed to designing long and multi-step projects.
Bonus: familiarity with the platforms and data sources we use (Stripe, HubSpot, PostHog, customer.io, Google Analytics).
Engagement:
Skills Required
- 3+ years of experience as a data scientist
- Hands-on with SQL and Python
- Ability to translate business questions into metrics
- Collaborate with data engineering team
- Familiarity with platforms like Stripe and HubSpot
AI Fund Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AI Fund and has not been reviewed or approved by AI Fund.
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Healthcare Strength — Health coverage is portrayed as strong with great healthcare and dental coverage, plus vision insurance, long-term disability, and life insurance. Feedback suggests this aligns with tech-standard benefits for US roles at a small venture studio.
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Retirement Support — Retirement benefits include a 401(k) plan with employer match for US employees. Feedback suggests this forms part of a competitive total package for fund roles.
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Parental & Family Support — Family support includes fully paid parental leave for applicable roles. Feedback suggests this is a standout benefit for an organization of this size.
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What We Do
Who is AI Fund? We are a team of AI pioneers, proven entrepreneurs, seasoned operators, and venture capitalists that collaborates with leading entrepreneurs to solve big challenges using artificial intelligence. Founded in 2017 by Dr. Andrew Ng, AI Fund is backed with $176 million in capital by some of the leading VC firms and investors, including NEA, Sequoia, and Greylock. How Are We Different? We work with entrepreneurs during their startup’s most critical and risky phase, from 0 to 1. At the earliest stages, your company strategy is still being formed, and you’re still on the path to demonstrating your idea’s full potential – this is a reality we understand. This is the period when decisions on product strategy, market fit, and team are most critical, moving fast and fixing parts of your business when you have limited resources is a challenge. We believe the best way to help entrepreneurs is by providing our time, expertise, and resources to help flesh out these key strategic decisions. Making the right decisions at the right time can often make the difference. We are here to improve these dynamics, at a time when the help matters the most. Why Work With AI Fund? Getting a startup from idea to Series A funding is not easy. We’ve been there and understand the challenges you must overcome. Whether you desire limited help and just want access to our unique ecosystems of AI experts and entrepreneurs or you would like our full support, we are interested in the opportunity to help in your success. We are flexible in how we work with companies, but ultimately, we are here to maximize your chance of success and accelerate getting your company to market. We provide the capital, expertise, and resources to accelerate the work required to minimize risks in your startup, help you rise above the noise, and make your company more attractive to new investors.
