Data Scientist - Operational Optimization & Workforce Strategy
Role details
Job location
Tech stack
Job description
We are seeking a highly skilled Data Scientist to lead advanced analytics and optimization initiatives supporting large-scale operational and workforce management challenges. This role will play a critical part in translating complex business problems into scalable data products, with a solid emphasis on enabling and accelerating our Palantir-driven ecosystem.
You will operate at the intersection of data science, operations research, and platform-based analytics-designing solutions that not only generate insights but are embedded directly into decision-making workflows. This role requires both technical depth and the ability to influence cross-functional stakeholders across operations, product, and engineering.
You'll enjoy the flexibility to work remotely* from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week., Advanced Modeling & Optimization
- Design, develop, and deploy statistical, machine learning, and optimization models to improve operational efficiency and workforce performance
- Build and enhance workforce management solutions including:
- Demand forecasting (time series, causal models)
- Capacity planning and scenario modeling
- Scheduling and resource allocation optimization
- Apply advanced optimization techniques (e.g., linear/integer programming, constraint optimization, simulation, heuristics)
Palantir & Data Product Enablement
- Develop scalable analytical solutions within Palantir Foundry, including:
- Data pipelines and transformation logic
- Operational data models / ontologies
- Decision-support applications and workflows
- Partner with engineering and platform teams to productionize models into reusable data products
- Ensure solutions are maintainable, interpretable, and embedded into business processes
Operational Strategy & Impact
- Translate ambiguous business problems into structured analytical frameworks
- Define and operationalize KPIs, metrics, and success criteria tied to business outcomes
- Identify inefficiencies and opportunities through deep analysis of large, complex datasets
- Drive measurable impact through experimentation, A/B testing, and continuous model monitoring
Stakeholder Leadership
- Partner closely with operations, workforce management, and product leaders to align solutions with business priorities
- Communicate complex analytical concepts and results to non-technical audiences
- Influence decision-making through data storytelling and actionable recommendations
Data Engineering & Scalability
- Build and maintain scalable data pipelines and analytical workflows
- Develop dashboards and monitoring tools to support ongoing operations
- Ensure data quality, governance, and model explainability
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in., * Operational decisions are increasingly data-driven and automated
- Forecasts and optimization outputs are trusted, adopted, and embedded in workflows
- Palantir solutions are scalable, reusable, and business-critical
- Measurable improvements in efficiency, cost, and service levels
- Solid partnerships with stakeholders and clear influence on strategic direction
Requirements
Do you have experience in Statistics?, * 4+ years of experience in data science, applied analytics, or operations research (higher bar helps filter)
- Experience working with Palantir Foundry or similar data platforms (Databricks, Snowflake + orchestration layers, etc.)
- Demonstrated proficiency in Python and SQL (R acceptable but Python preferred)
- Demonstrated experience building and deploying models in production environments
- Hands-on experience with operational optimization, workforce planning, or supply/demand systems
- Demonstrated foundation in:
- Statistics and machine learning
- Optimization techniques (LP, MIP, etc.)
- Proven ability to work with large, complex datasets and translate insights into business impact
- Proven communication skills with experience working cross-functionally, * Background in operations research, industrial engineering, or service operations
- Experience with optimization tools such as Pyomo, OR-Tools, Gurobi, or CPLEX
- Experience building end-to-end data products, not just models
- Familiarity with workforce management systems (e.g., NICE, Verint, Genesys)
- Experience with experimentation frameworks and causal inference
- Experience in healthcare operations, call center optimization, or large-scale service environments
- Experience working in matrixed enterprise environments
Key Skills:
- Workforce forecasting & demand modeling
- Capacity planning & scenario analysis
- Optimization modeling (LP/MIP/heuristics)
- Data product development (Palantir)
- Data visualization & storytelling
- Cross-functional leadership
Benefits & conditions
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $134,600 to $230,800 annually based on full-time employment. We comply with all minimum wage laws as applicable.