Who You Are:We're looking for a Data Scientist to help our marketplace business continue to innovate and grow. An ideal candidate will have professional experience building machine learning models that are used to predict business outcomes - such as customer propensity to spend, churn prediction, price forecasting, or other relevant areas - and, just as importantly, experience operationalizing those models so they run reliably in production without becoming a maintenance burden over time.
You should have a curious mind and an interest in how a marketplace business optimizes its growth, with a vision for how to ensure innovation, transparency, and cost-effectiveness at scale. You should also be comfortable partnering with stakeholders across the business - communicating your findings, building buy-in, and seeing your work through to real production impact. If you are looking to join a growing team within a growing company that's making data a priority, this is the role for you. You'll have the opportunity to touch many aspects of the business.
Core Responsibilities:- Support the organization as we experiment with new product features and strategies, helping to forecast and understand the impact of these changes.
- Build, deploy, and maintain machine learning models in production - operationalizing them in a sustainable, maintainable way.
- Collaborate with product, growth, and development teams to identify opportunities to incorporate a data science approach to product / feature development, and to drive experiments and initiatives through to a decision and into production.
- Assist with analysis of large volumes of transactional data to identify opportunities to create efficient, transparent, and low-cost marketplace interactions that drive growth.
Requirements- BA/BS in a quantitative field such as Statistics, Computer Science, Engineering, Mathematics, or Data Science.
- 3+ years of experience with machine learning models including development, version control, and deployment/serving of models.
- Demonstrated experience operationalizing ML models in production - either independently or alongside an engineering team.
- Experience working with platforms such as Snowflake and Databricks.
- Proficient in one or more programming languages, such as Python.
- Experience using AI tools to increase throughput for exploratory data analysis, model development, experimentation, and more.
- Strong planning, communication, and problem-solving skills.
Strongly Desired Attributes:- A track record of getting stakeholder buy-in and commitment on experiments and initiatives - communicating findings clearly, addressing concerns from the business, and ensuring that the results of your efforts lead to production impact.
- Experience with paid search and/or paid social, and with experimentation that supports growth teams in producing better user acquisition outcomes.
- Experience working with data modeling software and on teams with data modelers.
- Experience using analytical approaches to problem-solving with large volumes of data.
Nice to Have:- Experience with marketplace businesses and dynamic pricing.
- A demonstrated interest in related areas such as marketplaces, financial markets, or other related areas (hands-on experience a plus).
Benefits- A hybrid in-office approach, enabling remote work a portion of each week
- Health Care Plan (Medical, Dental & Vision)
- Retirement Plan Contribution (401k, IRA)
- Life Insurance (Basic, Voluntary & AD&D)
- Paid Time Off (Vacation, Sick & Holidays)
- Family Leave (Maternity, Paternity)
- Training & Development
- $100 Monthly Stipend to Attend Live Events
- Employee Outings
- Free Lunch & Snacks
The estimated pay range for this role, based in New York City, is $105,000 - $135,000. This role will be eligible to participate in our company's equity program. Our salary ranges are based on paying competitively for our size and industry, and are one part of many compensation, benefits, and other reward opportunities we provide.
Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.
The range above is for the expectations as laid out in the job description. However, we are often open to a wide variety of profiles and recognize that the person we hire may be less experienced (or more senior) than this job description as posted. If that ends up being the case, the updated salary range will be communicated to you as a candidate.
