Note: The job is a remote job and is open to candidates in USA. Appriss Retail provides omnichannel retail loss solutions that use unified data to reduce returns, shrink, and incidents for retailers. The Data Science Manager leads a small team while remaining hands-on, owning data engineering, governance, machine learning, production delivery, and LLM- and agentic-AI solutions. The role also guides architecture, mentors team members, and partners with product, engineering, and business stakeholders on data strategy and delivery.
Responsibilities
- 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 alongside your team; treat infrastructure as a first-class product concern
- Build, evaluate, and iterate on ML models in production; lead experimentation rigor, monitoring, and lifecycle management
- Architect and ship LLM-integrated features and agentic workflows — including prompt engineering, tool use, and output evaluation
- Guide cloud infrastructure architecture for data science projects, taking into account performance, maintenance, and cost criteria
- Set the standard for code quality: write production-grade Python and SQL, enforce review practices, and maintain documentation
- Partner closely with engineering to integrate models and pipelines into core product infrastructure
- Directly manage 2–4 data scientists; provide technical mentorship, career development, and clear performance expectations
- Define team operating norms: sprint planning, code review, documentation, and delivery accountability
- Recruit and grow the team as the function scales
- Translate ambiguous business problems into well-scoped analytical and modeling work with defined success criteria
- Partner with product, engineering, and business stakeholders to ensure data work is grounded in real source systems and product context — not isolated analysis
- Contribute to the data and analytics roadmap, balancing near-term delivery with longer-term platform investment
- Communicate clearly to non-technical audiences; influence decisions with data and model outputs
Skills
- Master's degree in a quantitative field, or bachelor's 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; production code, not just analysis scripts
- Deep understanding of data infrastructure: pipelines, warehousing, data modeling, and source system behavior
- Hands-on ML experience: model training, evaluation, deployment, monitoring, and iteration
- Strong software engineering practices: 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: Snowflake, Azure (preferred), AWS, or GCP
- Proficiency with modern data stack tooling: dbt, Airflow, Spark, or equivalent
- Demonstrated LLM experience: prompt engineering, RAG, fine-tuning, or agent frameworks (LangChain, LlamaIndex, or equivalent)
- Experience and familiarity with agentic AI architectures: multi-step reasoning, tool use, memory, and orchestration
- Experience in retail, fraud detection, or transaction-level data at scale
- Familiarity with ML platform tooling: MLflow, feature stores, model registries, or similar
Benefits
- Multiple medical plan options, beginning on your first day
- Dental and vision coverage, beginning on your first day
- Health savings and flexible spending accounts, beginning on your first day
- Paid parental leave, beginning on your first day
- Supplemental coverage for life’s unexpected moments, beginning on your first day
- Generous paid time off
- A 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 to help you grow your career
- Remote work in the United States
- This job is eligible for a 12-15% bonus in addition to the base salary.
Company Overview
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