Data Scientist, Avail

Role Description

We are seeking a Staff Data Scientist with a strong background in machine learning, experimentation, strategic analytics, and cross-functional stakeholder support to help shape the future of our Data Science program  a trusted partner to the Avail leadership team, you will be the vital link between complex data and pivotal business moves, striving to enable and empower data-driven decision making across the business.

In this role, you will analyze large and complex data sets, conduct robust analyses, generate actionable insights, and deliver clear recommendations that inform critical decisions across strategy, product, marketing, and operations.

The ideal candidate is a detail-oriented data science expert, a self-starter comfortable with ambiguity, and a team player who excels in cross-functional collaborations, with the ability to work in a fast-paced environment and driven by a desire to make things better.

• Partner closely with Avail business stakeholders to understand/clarify needs and requirements, and translate them into data science problems.
• If the required data is not available, work with the team to identify the right data sources, and build analytical data layers in collaboration with the data engineering partner.
• Independently conduct end-to-end data science work from data collection, ETL, model development/analysis, to the delivery of insights and recommendations.
• Serve as Avail’s Data Science expert and own experimental design and advanced statistical analysis best practices; provide consultation and collaborate closely with colleagues conducting research/experiments in product, marketing and beyond.
• Document methodologies, assumptions, and recommendations clearly for both technical and non-technical audiences.
• Build and grow adoption of self-service solutions that empower stakeholders to access data and insights, and hence accelerate data-driven decision making.
• Work with Avail leadership team on strategic initiatives and planning, providing analytical support on financial modeling, forecast, opportunity sizing, and so on.
• Foster a culture of accountability and transparency by ensuring reproducibility, traceability, and clear code documentation in all analytics work.

We balance creativity and innovation on a foundation of in-person collaboration. Our employees work three days in our Austin headquarters where they have the opportunity to collaborate in-person, adding richness to our culture and knitting us closer together.

® is committed to investing in the health and wellbeing of our employees and their families. Our benefits programs include, but are not limited to:

• Inclusive and Competitive medical, Rx, dental, and vision coverage
• Family forming benefits
• 13 Paid Holidays
• Flexible Time Off
• 8 hours of paid Volunteer Time off
• Immediate eligibility into Company 401(k) plan with 3.5% company match
• Tuition Reimbursement program for degreed and non-degreed programs
• 1:1 personalized Financial Planning Sessions
• Student Debt Retirement Savings Match program
• Free snacks and refreshments in each office location

• Bachelor’s degree in a quantitative field (e.g., Statistics, Data Science, Applied Mathematics, Economics, Engineering, Computer Science).
• 8+ years of relevant experience as a Data Scientist, Data Analyst, Product Analyst, or similar role, using SQL and Python (pandas, numpy, scipy).
• SQL & Python proficiency is a must, with 8+ years of experience.
• Strong capability to work with complex data sets and perform EDA, descriptive, diagnostic, and predictive analyses.
• Sound understanding of statistical methods for experimentation (randomization, t-tests, confidence intervals, etc.).
• Experience with cloud-based data environments such as Snowflake and AWS.
• Proven experience using data science to drive revenue and other business KPIs, and doing so in a proactive manner by actively seeking to identify opportunities.
• Excellent written and verbal communication skills, with experience presenting to diverse technical and business audiences at different levels.
• Experience in collaborating with cross-functional partners.
• Self-motivated and…