About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Retail Apparel and Fashion,Retail,Warehousing and Storage.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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What You’ll Do

Confidential Client is hiring an Associate Data Scientist to help turn customer, order, product, and sales data into insights, models, and AI-enabled tools. You will work closely with data scientists, data engineers, analysts, and business stakeholders to support data-driven decisions across the business.

• Analyze customer behavior across the e-commerce journey to identify trends that drive engagement, conversion, retention, and repeat purchases
• Support development of statistical and machine learning models: personalization, recommendations, customer segmentation, time series forecasting, clustering, regression, and classification
• Help build and maintain AI pipelines and LLM-powered tools; use Claude and Gemini to accelerate SQL and Python development while validating outputs
• Automate recurring reports, analyses, and data workflows; build dashboards (Amazon QuickSight) to track KPIs
• Collaborate with data engineers to understand sources, data models, and business definitions; extract, clean, and transform large datasets and prepare features for modeling
• Run causal and impact analyses to measure the effect of site and personalization changes and recommend improvements
• Deliver ad hoc analyses partnering with Merchandising, Operations, Sales, and Customer Experience to answer business questions quickly and accurately
• Present findings and recommendations to leadership in a clear, concise, and actionable way

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Qualifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Math, or another analytical discipline
• 2+ years of experience as a data analyst or in a data science role
• Strong programming skills in Python (Pandas, NumPy, Scikit-learn)
• Proficiency in SQL for querying and managing structured data
• Foundation in machine learning and statistical techniques (regression, classification, clustering, recommendation systems, time series forecasting)
• Experience with exploratory data analysis, feature engineering, and model evaluation
• Strong problem-solving skills and a habit of validating your own work
• Ability to communicate technical concepts and results to non-technical audiences

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Preferred Experience

• Master’s degree in a related field with 1+ year of experience (preferred)
• Familiarity with causal inference methods
• Experience with LLM APIs, prompt engineering, AI system design, and AI evals
• Experience with AWS services (Redshift, Bedrock) and Amazon QuickSight
• Experience with Git or other version control
• Experience in e-commerce or retail environments

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What We Offer

• Medical, dental, and vision coverage
• FSA options (medical, dependent care, commuter)
• Paid time off, paid sick time, and paid holidays
• 401(k) with generous match program
• Free life insurance and AD&D
• Long-term disability insurance
• Employee discount

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Compensation & Work Authorization

• Pay range for hires in California (this location): $90,000 - $110,000 per year. Final offer will vary based on location, candidate qualifications, and experience. This range is provided in compliance with applicable pay transparency requirements and is accurate as of the posting date.
• This position requires valid, ongoing U.S. work authorization. The client is unable to support visa petitions or transitions.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.