Data Science Project Manager

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

📋 Description

• Oversee the daily execution of various data science and machine learning initiatives.

• Convert business challenges and strategic goals into defined project scopes, objectives, milestones, deliverables, and criteria for success.

• Manage project plans, backlogs, roadmaps, timelines, dependencies, risks, decisions, and action items effectively.

• Collaborate with data scientists, data engineers, software engineers, ML engineers, product managers, and business stakeholders to coordinate efforts.

• Organize sprint planning, standups, retrospectives, status reviews, demonstrations, and project working sessions.

• Identify obstacles, drive resolutions, and escalate decisions as needed.

• Ensure that project documentation, requirements, assumptions, and decisions remain up-to-date and easily accessible.

• Deliver regular updates on progress, risks, dependencies, and anticipated outcomes.

• Monitor requirements for reproducibility, versioning, testing, deployment, monitoring, and documentation.

• Oversee model release readiness, production handoffs, and follow-ups after deployment.

• Ensure that teams prioritize data quality, model performance, drift, reliability, security, and ownership of support.

• Assist in establishing processes for model promotion, retraining, monitoring, incident response, and retirement of models.

• Develop scalable operational processes, templates, dashboards, meeting schedules, and documentation standards for the Data Science team.

• Recognize recurring delivery challenges and propose enhancements to processes, tools, roles, or decision-making frameworks.

⛳️ Requirements

• More than 5 years of experience in technical project management or a comparable delivery position.

• Proven experience in managing data science, machine learning, analytics, or similarly technical projects.

• Experience in coordinating cross-functional teams encompassing Data Science, Engineering, and Product functions.

• Capability to comprehend technical discussions related to data pipelines, experimentation, model evaluation, APIs, deployment, and production support.

• Strong project management skills, encompassing planning, prioritization, dependency management, risk management, and status reporting.

• Exceptional written and verbal communication abilities.

• Competence in navigating ambiguity and structuring complex, evolving tasks effectively.

• Keen attention to detail and commitment to follow-through.

• Experience in Agile, Scrum, Kanban, or similar delivery methodologies.

• Practical experience in utilizing AI within workflows responsibly and effectively.

• Solid understanding of the data science and machine learning lifecycle.

• Familiarity with MLOps, ML platforms, or production-grade machine learning systems.

• Knowledge of model deployment, model registries, experiment tracking, CI/CD, workflow orchestration, model monitoring, data quality monitoring, and retraining processes.

• Awareness of responsible AI, model risk management, privacy, explainability, bias, or regulatory considerations.

• Technical expertise in data science, computer science, engineering, analytics, mathematics, or a related field.

🏝️ Benefits

• Health, dental, and vision insurance coverage.

• Retirement savings plan with company matching contributions.

• Paid time off and recognized holidays.

• Opportunities for professional development.

• Performance-based bonuses related to the position.

• Additional rewards, including an annual bonus and sales incentives, based on applicable plans, roles, and individual performance.