Data Science Manager

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Appriss Retail

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Appriss Retail is a company that specializes in providing solutions to prevent fraud and shrink in the retail industry. For over 25 years, they have been helping retailers protect their profits against fraudulent and abusive returns, claims, and appeasements. Their solutions, such as Appriss Secure, Appriss Engage, and Appriss Incident, use AI-based analytics and real-time transaction analysis to identify and resolve instances of shrink or margin erosion. Appriss Retail is trusted by over 60 of the top 100 U. S. retailers.

📋 Description

• Own end-to-end delivery of high-impact data science projects from ambiguous business request to production-ready system • Design and maintain data pipelines, data models, and governance standards • Build, evaluate, and iterate on production ML models • Lead experimentation rigor, monitoring, and lifecycle management • Architect and ship LLM-integrated features and agentic workflows • Guide cloud infrastructure architecture for data science projects • Write production-grade Python and SQL and enforce code review and documentation practices • Partner with engineering to integrate models and pipelines into core product infrastructure • Directly manage 2–4 data scientists and provide technical mentorship and career development • Define team operating norms and delivery accountability • Recruit and grow the team • Translate ambiguous business problems into scoped analytical and modeling work • Partner with product, engineering, and business stakeholders • Contribute to the data and analytics roadmap • Communicate technical findings and influence decisions with data and model outputs

🎯 Requirements

• Master’s degree in a quantitative field, or bachelor’s degree with significant professional experience • 6+ years of experience in data science, data engineering, or a closely related technical discipline • 1+ year of direct people management or formal technical lead experience over a team • Expert-level SQL and Python, including production code • Deep understanding of data infrastructure, pipelines, warehousing, data modeling, and source system behavior • Hands-on ML experience with model training, evaluation, deployment, monitoring, and iteration • Strong software engineering practices, including version control, code review, testing, and CI/CD familiarity • Ability to scope and deliver complex analytical projects independently from vague inputs • Cloud data platform experience with Snowflake, Azure, AWS, or GCP • Preferred: modern data stack tooling such as dbt, Airflow, or Spark • Preferred: LLM experience including prompt engineering, RAG, fine-tuning, or agent frameworks • Preferred: familiarity with agentic AI architectures including multi-step reasoning, tool use, memory, and orchestration • Preferred: experience in retail, fraud detection, or transaction-level data at scale • Preferred: familiarity with ML platform tooling such as MLflow, feature stores, or model registries

🏖️ Benefits

• Multiple medical plan options • Dental and vision coverage • Health savings and flexible spending accounts • Paid parental leave • Supplemental coverage for life’s unexpected moments • Generous paid time off • 401(k) with immediate vesting and company match • Short- and long-term disability • Free access to health and wellbeing resources such as Calm and Sworkit • Learning and development opportunities • 12–15% bonus in addition to the base salary • Minimal optional travel