Staff Data Scientist

Austin, TX - USA

Monthly Salary: Not Disclosed

Posted on: 16 hours ago

Vacancies: 1 Vacancy

Job Summary

CSC Generation operates $1B in revenue across 13 retail brands including Sur La Table Backcountry One Kings Lane and more. Pricing is central to how we compete and were building the kind of ML-driven pricing capability that the best e-commerce companies in the world have invested in for years.

Were looking for a Staff Data Scientist whos an expert in building and shipping production pricing systems demand forecasting price elasticity modeling dynamic pricing and the experimentation infrastructure that tells you whether any of it is actually working.

Its a hard problem with real data real stakes and real business impact. If youve spent time thinking carefully about how to measure price sensitivity at scale how to run pricing experiments without destroying margin or how to build forecasting systems that hold up in production this is your role.

What Youll Own

Design and build production ML systems for pricing demand forecasting and related revenue problems
Frame ambiguous business problems as well-defined ML tasks with clear success criteria and measurable outcomes
Set the standard for model evaluation validation and monitoring including knowing when CV metrics are misleading and when holdout testing is the only honest answer
Build robust predictive models across classification regression time series and causal inference
Identify and prevent data leakage overfitting and other failure modes before they reach production
Design and analyze experiments to measure causal impact of pricing decisions
Debug models that fail in production understand why they fail not just that they do
Translate model limitations uncertainty and risk clearly to both technical and non-technical stakeholders
Partner with product engineering and business teams to ensure ML solutions solve real problems

Who Were Looking For

7 years of applied ML / data science experience with a track record of production systems that delivered measurable business impact.
Deep pricing demand forecasting or revenue optimization experience. Youve built these models not just used them.
Expert-level Python and SQL.
Strong grounding in causal inference and experimental design. You know the difference between a correlation and a result.
Ability to work with messy real-world data and make pragmatic tradeoffs.
Familiarity with cloud ML platforms (GCP/Vertex AI or AWS/SageMaker).
MS or PhD in Statistics Computer Science Operations Research or a related quantitative field.
Self-directed and autonomous. You dont need the problem handed to you fully formed.
Experience in e-commerce retail marketplace or pricing-intensive industries (airlines ride-sharing fintech).

Who Were Not Looking For

Someone who only knows how to call .fit() and .predict() without understanding the underlying mechanics.
Someone who builds black-box models they cant explain debug or justify.
Someone who needs detailed instructions or hand-holding for ambiguous problems.
Someone who over-engineers solutions when a simple approach would suffice.

For US-based candidates this posting is intended for candidates thatresidein the following states:

AZ DE FL GA IN LA MI MS MO NV NC OK PA TN TX UT WV WIandWY.

Our preference is for candidates whoresidenear our hubs in Northwest Indiana Austin Texas and Toronto Ontario.

Washington state applicants only: If you believe that this job posting does notcomply withapplicable Washington state law pleasenotify usby sending an email toemailprotected.

We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.

Required Experience:

Staff IC