Staff Data Scientist– Pricing Science
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Job Location:
Austin, TX - USA
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
CSC Generation is the AI-native holding company re-engineering omnichannel retail. We acquire iconic brands and transform them with Genesis our operating platform combining a Data Fabric Automation Engine proprietary tools and shared services to modernize operations elevate customer experience and expand margins. With $1B in revenue across 13 brands our portfolio includes Sur La Table Backcountry One Kings Lane and others that serve as real-world innovation labs.
Reports to: Director of Finance and Business Intelligence
Location: Remote US or Canada
About the Role
As our Staff Data Scientist you will design and ship production pricing systems such as demand forecasting price elasticity modeling dynamic pricing and the experimentation infrastructure needed to measure whether they actually work.
This is a hard high-stakes problem: your models will directly influence margin and revenue decisions across a portfolio of brands operating at scale. You will own the full arc from framing ambiguous business problems as well-defined ML tasks through to monitoring models that hold up in production.
At six months success looks like at least one pricing model shipped to production with measurable business impact and an experimentation framework in place that your stakeholders trust. If you have spent time building pricing systems from the ground up not just consuming them and you care deeply about rigorous causal inference and honest model evaluation this role was written for you.
What Youll Do
- 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
Required Qualifications
- 7 years of applied ML / data science experience with a track record of production systems that delivered measurable business impact.
- Deep experience in pricing demand forecasting or revenue optimization you have built these models end-to-end not just consumed them.
- Expert-level Python and SQL.
- Deep understanding of ML fundamentals beyond API-level usage including model evaluation validation and failure mode diagnosis.
- Strong grounding in causal inference and experimental design including the ability to distinguish correlation from causal result.
- Ability to work with messy real-world data and make pragmatic tradeoffs under ambiguity.
- 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.
Preferred Qualifications
- Experience in e-commerce retail marketplace or pricing-intensive industries such as airlines ride-sharing or fintech.
Why Join
The people who do best here are builders. They take ownership move fast and want to see the direct impact of their work.
- Portfolio-Level Impact: Your models will influence pricing and margin decisions across a $1B portfolio of brands the output of your work is visible at the executive level from day one.
- AI-First Skill Building: Get hands-on with production ML infrastructure causal inference at scale and the Genesis platform building a modern applied ML skill set on real retail data problems.
- Ownership: You will own the full problem from framing through production with the autonomy to make technical decisions and the stakeholder access to see them through.
- Competitive Benefits (CAN): Comprehensive benefits including paid time off RRSP match group benefits and employee discounts across portfolio brands.
- Competitive Benefits (US): Comprehensive benefits including paid time off 401(k) match medical dental vision supplemental coverage and employee discounts across portfolio brands.
Interview Process
- Recruiter Screen: 30-minute call to cover your background the role and logistics.
- Hiring Manager Interview: Conversation with the Director of Finance and Business Intelligence focused on your pricing science experience approach to ambiguous ML problems and how youve driven production impact.
- Technical / Case Discussion: Deep dive into a pricing or demand forecasting problem expect questions on model evaluation causal inference and production failure modes. Cross-functional stakeholders may join.
- Executive Interview: Final conversation with senior leadership.
- Reference Checks: Conducted in parallel with the final stages where possible.
- Offer: We move quickly for the right candidate.
For US-based candidates this posting is intended for candidates that reside in the following states:
AZ DE FL GA IN LA MI MS MO NV NC OK PA TN TX UT WV WI and WY.
For Ontario applicants please note that this posting is for an existing vacancy.
The CSC Generation family of brands provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal provincial state or local laws.
The CSCGenerationfamily of brands is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or accommodation due to a disability please contactemailprotected.
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
Key Skills
About Company
CSC Generation acquires and transforms businesses to drive growth. Discover how our expertise can help take your business to the next level.
