Data Scientist (Noom)

About Pyyne Pyyne is a modern technology consultancy engineering the next generation of digital products and services. At Pyyne, we believe in using technology to unlock business potential, create sustainable growth, and drive forward digital excellence. Our solutions range from advanced Software Engineering, Cloud, and Data & AI solutions. Job Summary Our client is a prominent NYC-based health tech company. They are seeking a mid-level Product Data Scientist to conduct product analysis and help design & evaluate A/B tests. The Product Data Science team currently consists of 4 other Data Scientists, who work together to tackle a variety of projects each week. A successful candidate in this role will be comfortable working closely with stakeholders across the data and business teams. Key Responsibilities Product Analysis: Answer insightful analysis questions from stakeholders across the Product org Be able to ramp up on how different parts of the product & data model function, to pull accurate results Partner with PMs and Engineers to design key metrics for different initiatives Experiment Analysis: Be the “stats expert” alongside PMs to ensure the design of effective experiments 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 Specific Deliverables (First 3-6 months): Ramp up on a particular product area and start answering ad hoc insight questions from there 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 Must Have Skills: 3 - 5 years of experience as a data scientist, in a product-focused environment 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) General understanding of machine learning, and how to make and evaluation models 🚀 Don’t meet every single requirement? Apply anyway! At our core, we value growth, adaptability, and passion just as much as a checklist of skills. If you are excited about this role and your experience doesn't align perfectly with every tech requirement, we still encourage you to apply. The only non-negotiable for us is fluent English , as you'll be collaborating daily with global teams. If you’ve got the language skills and the drive to learn, you might be exactly who we are looking for to bring a fresh perspective to our team!