Data Science Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the complete delivery process of impactful data science projects, from unclear business requests to fully operational systems.

• Design and sustain data pipelines, data models, and governance standards.

• Develop, assess, and refine production machine learning models.

• Lead the rigor of experimentation, monitoring, and lifecycle management.

• Architect and implement features integrated with LLM and agentic workflows.

• Direct the cloud infrastructure architecture for data science initiatives.

• Write production-level Python and SQL code while enforcing best practices in code review and documentation.

• Collaborate with engineering teams to incorporate models and pipelines into the core product architecture.

• Manage a team of 2–4 data scientists, providing technical guidance and fostering career development.

• Establish team operating norms and ensure accountability in delivery.

• Recruit and expand the team.

• Convert ambiguous business challenges into well-defined analytical and modeling tasks.

• Collaborate with product, engineering, and business stakeholders.

• Contribute to the strategic data and analytics roadmap.

• Present technical findings to influence decisions based on data and model outputs.

⛳️ Requirements

• Master’s degree in a quantitative discipline, or a bachelor’s degree with substantial professional experience.

• Over 6 years of experience in data science, data engineering, or a related technical field.

• At least 1 year of direct management experience or formal technical leadership over a team.

• Proficiency in SQL and Python at an expert level, including experience with production code.

• In-depth knowledge of data infrastructure, pipelines, warehousing, data modeling, and behavior of source systems.

• Hands-on experience with machine learning, including model training, evaluation, deployment, monitoring, and iteration.

• Strong software engineering practices, encompassing version control, code review, testing, and familiarity with CI/CD.

• Capability to independently scope and deliver complex analytical projects from vague inputs.

• Experience with cloud data platforms such as Snowflake, Azure, AWS, or GCP.

• Preferred: proficiency in modern data stack tools such as dbt, Airflow, or Spark.

• Preferred: experience with LLM, including prompt engineering, RAG, fine-tuning, or agent frameworks.

• Preferred: knowledge of agentic AI architectures, such as multi-step reasoning, tool utilization, memory, and orchestration.

• Preferred: background in retail, fraud detection, or working with transaction-level data at scale.

• Preferred: familiarity with ML platform tools like MLflow, feature stores, or model registries.

🏝️ Benefits

• Various medical plan options available.

• Coverage for dental and vision needs.

• Health savings and flexible spending accounts.

• Paid parental leave policy.

• Additional coverage for unforeseen life events.

• Generous paid time off policy.

• 401(k) plan with immediate vesting and a company match.

• Short-term and long-term disability coverage.

• Complimentary access to health and wellness resources like Calm and Sworkit.

• Opportunities for learning and development.

• Bonus structure of 12–15% in addition to base salary.

• Minimal optional travel requirements.