Dar / Urban Intelligence Lab (UIL)
Location: Bangalore, India (with global collaboration)
Work Type: Full Time
Company Overview:
Dar, the founding member of the Sidara group, is an international multidisciplinary consulting organization specializing in engineering, architecture, planning, environment, project management, facilities management, and economics. Sidara operates in over 60 countries with 20,500 professionals, connecting people, places, and communities through innovative solutions to the world's most complex challenges.
About the Urban Intelligence Lab (UIL):
UIL is Dar's data and AI-driven research and innovation unit focused on transforming how cities are understood, planned, and designed. Operating at the intersection of urban analytics, data science, and spatial intelligence, the lab applies cutting-edge methods - from mobility data to machine learning - to reveal hidden patterns of urban life and inform evidence-based planning and design decisions across Africa, the Middle East, and beyond.
Job Description:
The Lead Urban Data Scientist is a senior contributor role with team leadership responsibilities, you will shape the methodological direction of the UIL, drive high-impact research projects, and provide hands-on mentorship to a growing team of data scientists and analysts. You will work across the projects form Africa, the Middle East, and South Asia, translating cutting-edge data science into evidence-based urban planning insights for governments, multilateral institutions, and private clients.
Key Responsibilities
- Own end-to-end delivery of flagship urban analytics projects from data acquisition and pipeline design through spatial modelling, insight generation, and stakeholder presentation.
- Define and enforce methodological standards for the team, including reproducible workflow design, code review practices, and documentation protocols.
- Lead the design and implementation of advanced spatial models: land-use regression, accessibility indices, spatial interaction models, agglomeration/productivity analysis, and mobility pattern inference.
- Build and oversee scalable data pipelines for large geospatial, mobility, and remote-sensing datasets using distributed processing frameworks (PySpark, Dask, DuckDB).
- Integrate multi-source urban datasets -mobility traces, POI layers, census microdata, satellite imagery, transport networks -into coherent analytical frameworks.
- Translate complex analytical outputs into compelling policy narratives, dashboards, and visualisations for non-technical audiences including government ministries and C-suite clients.
- Manage and mentor data scientists; conduct regular technical reviews and guide their professional development.
- Contribute to business development by supporting proposal writing, scoping new engagements, and representing UIL in client meetings and conferences.
- Lead or co-author applied research outputs, white papers, and innovation initiatives that advance UIL's external visibility.
Qualifications and Experience
- Master's or PhD in Urban Economics, Data Science, Spatial Analysis, Geoinformatics, Urban Planning, or a closely related discipline.
- 5-10 years of professional experience applying data science to urban, spatial, and infrastructure challenges; at least 2 years in a lead or principal capacity.
- Expert-level Python skills: pandas, geopandas, NumPy, scikit-learn, and visualisation libraries (matplotlib, plotly, kepler.gl, or equivalent).
- Deep expertise in spatial data structures, coordinate reference systems, and vector/raster processing (GDAL, Rasterio, Fiona).
- Proven track record designing and managing large spatial databases (PostgreSQL/PostGIS) and distributed processing workflows.
- Strong background in at least two of: econometrics/causal inference, machine learning for spatial data, transport demand modelling, or urban remote sensing.
- Demonstrated ability to produce client-ready deliverables and communicate with senior non-technical stakeholders.
- Experience line-managing or mentoring analysts in a professional setting.
Desirable Skills
- Experience working on urban projects in Africa, the Middle East, or other Global South contexts.
- Familiarity with multilateral institution workflows (World Bank, AfDB, UNDP, GIZ) and their data standards.
- Proficiency with cloud platforms (AWS, GCP, or Azure) and workflow orchestration (Airflow, Prefect).
- Experience with satellite imagery pipelines, night-light analysis, or change-detection workflows.
- Background in urban systems modelling: transport models, land-use transport interaction (LUTI), or agent-based simulation.
- Published in disseminated research outputs (journals, conference proceedings, or technical reports).
Familiarity with containerised deployments (Docker) and API development (FastAPI).
