AI-First Data Scientist

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: VP Location: Remote - US What You'll Do

Design, build, and deploy machine learning models end-to-end — from data exploration and feature engineering through production deployment and monitoring.

Integrate AI and predictive models directly into business decision loops, including pricing optimization, demand forecasting, customer segmentation, and personalization.

Develop reusable data science products and frameworks that can be applied across multiple brands within the CSC Generation portfolio.

Partner with engineering, product, and analytics teams to translate business questions into well-scoped, technically rigorous problem statements.

Evaluate emerging AI tools and methods, recommending and prototyping solutions that advance our Genesis platform capabilities.

Document model logic, performance benchmarks, and deployment decisions to create institutional knowledge and enable cross-team reuse.

Champion AI-first thinking across the organization by leading knowledge-sharing sessions and contributing to internal best practices.

Required Qualifications

4+ years of experience in data science, machine learning, or a closely related applied role.

Demonstrated experience taking ML models from experimentation to production in a business environment.

Proficiency in Python and relevant data science libraries (e.g., scikit-learn, XGBoost, PyTorch, or TensorFlow).

Strong command of SQL and experience working with large-scale structured and unstructured datasets.

Experience with cloud data platforms (e.g., Snowflake, BigQuery, Databricks, or equivalent).

Ability to communicate model outputs and technical tradeoffs clearly to non-technical stakeholders.

Experience applying ML to e-commerce, retail, or consumer data domains (e.g., pricing, demand, churn, or recommendations).

Preferred Qualifications

Experience building or fine-tuning large language models (LLMs) or integrating GenAI APIs into production workflows.

Familiarity with MLOps tooling for model versioning, monitoring, and automated retraining (e.g., MLflow, Weights & Biases, or similar).

Background working in a multi-brand, holding company, or platform environment where solutions must scale across business units.

Experience with real-time or near-real-time model serving infrastructure.

Prior work on AI governance, model explainability, or bias/fairness frameworks.

Why Join

Impact & Visibility: Your models will run in production across 13+ brands, shaping real business decisions — not sitting in a notebook or a slide deck. Leadership sees and values the work data science does here.

Growth & Learning: You will work at the intersection of classical ML and emerging AI, with direct exposure to LLMs, automation, and a modern data stack being actively built and evolved. You will grow your skills on real, complex problems.

Ownership & Autonomy: You will define how problems get scoped, which approaches get tested, and what gets built. There is no bureaucracy between a good idea and putting it into production.

Competitive Benefits: We offer medical, dental, and vision coverage, a 401(k) with company match, paid time off, and remote work flexibility for US-based employees.

Our interview process:

1. Recruiter Screen: A member of our recruiting team will reach out to learn about your background and introduce CSC Generation.

2. Technical Challenge: You will complete a short AI or data science challenge so we can understand how you approach problems and execution.

3. Deep-Dive Interviews: You will participate in interviews with CSC leadership focused on your technical experience, problem-solving approach, and cross-functional collaboration skills.

4. In-Person Interview: You will meet with team members and leadership to discuss your approach, work style, and cultural alignment.

5. Reference Checks: We will connect with professional references to learn more about your working style and impact.

6. Offer: We extend an offer and welcome you to the team.