Position Overview
Senior Data Scientist - Urban Mobility and Location Intelligence at Motionworks – a leader in population intelligence that transforms billions of GPS traces into actionable insights for retailers, advertisers, urban planners, and transportation agencies across North America.
This applied research and modeling role requires you to design, defend, and validate statistical models that interpret travel behavior on a population level. The position is On-Site (3+ days/week) in San Diego, California (Little Italy). Compensation: $200k-$240k.
Applicants must be legally authorized to work in the United States; this role is not eligible for employer-sponsored work visas.
Key Responsibilities
- Design and validate Bayesian inference models to extrapolate observed location data to unobserved populations.
- Develop methods to distinguish personal travel from commercial delivery patterns in ambiguous GPS traces.
- Build statistical frameworks for handling varying data quality and data penetration rates across geographies.
- Create defensible models for trip purpose inference, stay-point detection, and behavioral segmentation.
- Write concise technical documentation to explain methodologies to internal stakeholders and clients.
- Prototype approaches that engineering teams can translate into production pipelines using Python, SQL, or other cloud tools.
- Recommend new data acquisitions and validation techniques to improve model performance.
Required Qualifications
- 8-10 years of applied experience working with large-scale location, mobility, or behavioral data; or a Master's/PhD with demonstrated applied work in transportation/retail analytics.
- Proven experience at scale with messy, real-world datasets (hundreds of millions of records, imperfect data quality, and sparse observations).
- Deep statistical foundations with the ability to derive likelihood functions and explain model assumptions while defending methodological choices with mathematical rigor.
- Expertise in Bayesian inference, including hierarchical models, prior specification, and uncertainty quantification.
- Strong technical skills in Python (e.g., NumPy, pandas, scikit-learn, statsmodels, PyMC) and SQL for complex queries in BigQuery/Spark environments.
- Solid domain intuition regarding urban mobility and transportation theory.
Preferred Qualifications
- Experience at a technology company working on mobility or logistics problems at a global scale.
- Familiarity with travel behavior concepts such as trip chaining, mode choice, and destination modeling.
- GIS/geospatial analysis skills (e.g., PostGIS, H3, spatial joins).
- Exposure to travel survey data (NHTS, household travel surveys).
Benefits & Perks
- Medical, dental, and vision coverage for you and your dependents.
- Paid Time Off: Two weeks of PTO in the first year, and four weeks thereafter.
- 14 holidays and flex holidays.