FabFitFun is one of the best places to work and its amazing success (over 1 million members) has been achieved due to our incredible employees, dedicated leadership, inclusive corporate culture, and career growth opportunities. Guided by our company values, FFF seeks to maintain a work culture that encourages innovation, rewards creativity, values teamwork, and supports diversity, equity, and inclusion. The company endeavors to foster confidence, effectiveness, and success for all employees who work with these values every day.

We have a new opportunity for a Data Scientist to play an impactful role in a diverse Machine Learning (ML) organization responsible for building algorithmically powered customer-facing data products and internal decision science tools. You will use machine learning and statistical models to analyze and solve problems, clean and explore data, test and deploy data services and tune and optimize existing algorithms. Our centralized team works with various departments on multiple projects with this role initially focusing on building cutting-edge algorithms to help automate inventory curation, optimization and personalization at scale.

What We’re Like:

• A collaborative learning culture: we work as a team to figure out solutions to the technological challenges of the day 
• We focus on improving our customer's experience every day, all the while taking the time necessary to make sure we do things the best we can 
• We celebrate innovation and want every member at FFF to have the power to experiment and find novel, effective solutions

What You’ll Do:

• Create, engineer and train multiple statistical and machine learning models and features in Python or R and SQL.
• Utilize AWS, Databricks and other tools to build data-processing and storage pipelines that can scale to millions of rows with high performance.
• Working with your manager, write code that can be included in modules or services that are in production in the data pipelines of customer-facing services.
• Provide feedback, suggest revisions and paths for improvements to models and analyses from other team members.
• Write clear documentation, model descriptions and results from analyses to explain results and architecture to other team members, business stakeholders and executives.
• Work with business stakeholders and project leads to identify goals and milestones for data products and to develop plans over multiple releases and timescales (including architecture, major models to test and deliverables) to achieve those milestones.
• Independently set day-to-day priorities that advance project goals.
• Partner and participate with business stakeholders and executives in meetings for requirements-gathering and coordination.

What You’ll Bring:

• Degree (M.S. or Ph.D. preferred) in Statistics, Economics, Engineering, Computer Science or related quantitative field. 
• One to three years hands-on work experience in statistics, data science and machine learning.
• The ability to clarify, solve and communicate complex business problems with solutions that are useable by non-technical audiences.
• Knowledge of machine learning algorithms (e.g., clustering, regression, classification, optimization, etc.) and statistical inference.
• Experience with Python, R, SQL, Spark or similar languages.
• Experience using distributed computing tools to scale jobs and processing for very large datasets is a preferred.
• Experience in consulting and/or subscription e-commerce, retail or related domains is a plus.

What You’ll Get: 

• Competitive salary, equity incentives and an amazing benefits package including medical, dental, vision, FSA and 401k
• The​​ opportunity​ ​to​ ​work​ ​in​ ​a​ ​collaborative environment​ ​full​ ​of​​ bright, driven, and happy​ ​people​
• Be a part of one of the fastest growing companies in the US that is revolutionizing eCommerce
• Open/Flexible PTO policy - we trust our employees to manage their time!
• Free FabFitFun subscription and quarterly credit in the Add-Ons store
• Monthly cell phone reimbursement
• Monthly work from home stipend while the company is temporarily remote