Lead Data Scientist

We're seeking a Sr Data Scientist & Geospatial Data Analyst who combines the rigor of a Product Data Scientist with the investigative depth of a Last-Mile Delivery Data Analyst. In this hybrid role, you will analyze geospatial and delivery data, build evaluation frameworks, influence routing and map content improvements, and shape product strategy through enterprise customer insights. You will join the Enterprise Solution product team and become the data detective who uncovers insights that drive our product forward. You'll dive deep into geospatial data, logistics planning and execution patterns, and system performance metrics to identify problems, spot opportunities, and guide algorithmic improvements. Your analysis will directly influence how our customers optimize last-mile planning and execution down to the last meter. This isn't just about generating reports-you'll be an integral part of the product development cycle, working closely with engineers and product managers to translate data insights into actionable improvements. You'll build the dashboards and monitoring systems that help us maintain quality, expand coverage, and continuously improve our delivery optimization algorithms. This role is ideal for a geospatially fluent data analyst with strong problem-solving skills, capable of working with large, complex datasets and influencing product direction through clear insights.

What you'll do:

Last mile delivery and logistics optimization

• Analyze delivery and sensor data to extract last meter location insights
• Proactively identify coverage gaps and algorithmic problems before they impact customers.
• Guide improvements to routing, location matching, and optimization models.
• Conduct geospatial analyses to assess location accuracy and delivery efficiency.

Enterprise customer and map gap quality insights

• Detect gaps, anomalies, and product issues using telemetry, API logs, customer signals, and usage data and translate insights into product improvements, KPIs, and roadmap recommendations.
• Generate actionable insights from customer product usage and design data feedback loops to improve map coverage and content quality
• Build scalable data pipelines and automated monitoring systems for continuous evaluation

Dashboards and communication

• Build dashboards for map quality, delivery performance, and operational KPIs
• Create automated reporting and alerting systems for critical metrics
• Communicate insights clearly to technical and non-technical stakeholdeers and drive strategic product decisions

Cross-functional collaboration

• Work closely with Product, Engineering, Map Content, Data Engineering, and ML teams to integrate insights into product development.
• Champion data-driven decision-making and data feedback loops

• Master's or PhD in Data Science, Computer Science, Geoinformatics, Statistics, or equivalent experience
• 5+ years in data science, analytics, or geospatial analysis
• Hands-on experience with geospatial analysis tools and libraries (GeoPandas, PostGIS, Shapely, etc)
• Strong skills in SQL, Python (pandas, numpy, matplotlib, seaborn, or similar libraries), and data engineering (Spark, ETL, Kafka)
• Experience analyzing API logs, device telemetry, or anomaly detection
• Demonstrated ability to identify patterns and anomalies in complex datasets and turn analytical findings into product improvements
• Experience building dashboards and visualizations (Tableau, Grafana, Quicksight)
• Experience with agentic AI tooling and motivation/interest to grow in this area
• Strong analytical thinking with ability to translate data insights into product improvements
• Excellent communication skills-able to explain technical findings to diverse audiences
• Self-motivated with ability to proactively identify problems and propose solutions

Nice to have:

• Background in mapping or GIS
• Background in logistics optimization, routing algorithms, or operations research
• Background in quality assurance or data validation in production systems
• Experience with enterprise customer data or B2B ecosystems.
• Experience working with ML models - performance evaluation, bias, clustering, outlier detection
• Experience working with statistical analysis, A/B testing, real-time monitoring, or data validation frameworks.
• Exposure to Jupyter notebooks, version control (Git), and collaborative data analysis workflows

What do we offer?

• A great work-life balance
• Hybrid model of work
• Challenging problems to solve
• Collaborative and encouraging colleagues
• Opportunities to learn, grow and develop
• Regular feedbacks
• Flexible working hours
• Competitive salary plus bonus
• Employee wellness programs and life-coaching sessions
• Diverse team of fantastic & talented people from 60+ countries worldwide.