The Product Data Science team at Noom (www.noom.com) is seeking a mid-level Data Scientist Contractor. The primary responsibility is to conduct product analysis and help design & evaluate A/B tests.
Noom is more than just a health-tech company — it’s a mission-driven organization that has helped over 50 million users worldwide build healthier habits through science-backed behavioral psychology. Backed by $650M+ in funding and recognized by Forbes as one of America’s Best Startup Employers, Noom is scaling rapidly. If you’re looking to work on a product that genuinely changes lives — this is the place.
The Product Data Science team currently consists of 4 other Data Scientists, who work together to tackle a variety of projects each week. We sit alongside the Business Data Science team (also 4 people) and the BI Engineering team.
“Product” at Noom covers all our in-app programs and features (including Noom Med!), as well as our Growth efforts (i.e. how we position and price their different product offerings!).
Key Responsibilities: * Product Analysis:
• Be able to ramp up on how different parts of the product & our data model function, to pull accurate results • Partner with PMs and Engineers to design key metrics for different initiatives • Answer insightful analysis questions from stakeholders across the Product org * Experiment Analysis:
• Understand and be able to intuitively explain concepts like power & sample size • Analyze experiment results to determine what is statistically significant, being able to take into account common pitfalls and “p-hacking” that can happen with A/B testing • Be the “stats expert” alongside PMs to ensure we design effective experiments * Specific Deliverables (First 3-6 months): • Design an experiment (with another Product DS there to mentor), see it launch, and then analyze it • Give feedback on new team processes and come up with an idea to iterate/make a new one • Ramp up on a particular product area and start answering ad hoc insight questions from there
Requirements: * Strong proficiency in SQL and a solid understanding of data modeling concepts * Proficiency with Python, ideally data analysis/science packages like Pandas and Stats * Good “Data storytelling” and stakeholder communication: can explain technical concepts in an intuitive way * Detail-oriented: can sense-check your output and correct errors before sharing results with stakeholders * A good product-sense and familiarity with fundamental “product” metrics (like DAU, retention, etc)
What We Offer: * Strong goal-oriented team, and a research mindset * Opportunity to leverage your engineering skills for fellow engineers and shape the future of AI * Working with the newest technical equipment * 20 working days of annual vacation leave * English courses, Educational Events & Conferences * Medical insurance
Про компанію DataRoot Labs DataRoot Labs is a full-cycle AI R&D center and the largest talent & compute pool in Ukraine.
We help companies like IBM, Noom, and Cognyte to co-build AI components into their core.
DataRoot Labs offers consulting & development for SMBs and enterprises from Los Angeles to Tel Aviv, leveraging:
— LLMs Training & Tuning (making LLMs say what you want them to — instead of infinite prompt engineering iterations) — Multimodal LLMs (making LLaMa able to see) — Vector DB design (developing to have a conversation with your data) — Reinforcement Learning (making robots more agile and smart)
In 8+ years in business, we’ve completed over 45 AI-enriched projects for numerous industry leaders and startups across Automotive, Energy & natural resources, Navigation, Gaming, Education, and many more. Some of them have become DataRoot Labs long-term partners, and trusted us to co-develop them.
Our agile Ukraine-based team of 50+ cross-domain professionals calibrates clients’ needs and evolves along with them. Beyond client work, DataRoot Labs conducts a free advanced trainee program, DataRoot University, offering practical skills and experience in Data Science & Engineering. Since 2017, over 1200 Ukrainians completed the course. Сторінка компанії
