[Hiring] Product Data Scientist @Pyyne

Role Description

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.

Qualifications

• 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 evaluate models.

Requirements

• Fluent English, as you'll be collaborating daily with global teams.

Benefits

• 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.