Key Responsibilities:

Problem Solving &amp; Technical Expertise:

<ul>
<li style="margin-left:0px;">Acquire, clean, and process structured and unstructured datasets, including data from household-level socio-economic surveys, published statistics, and multi-source satellite imagery</li>
</ul>

<ul>
<li style="margin-left:0px;">An ability to develop and implement methodologies for classification, change detection, and spatial modelling, applying geo-statistical and spatial statistical techniques, will be a plus</li>
</ul>

<ul>
<li style="margin-left:0px;">Apply machine learning approaches (e.g., random forests, gradient boosting, CNNs) to large datasets with experience in cloud computing (Azure, GEE) and distributed systems for large-scale spatial analysis</li>
</ul>

<ul>
<li style="margin-left:0px;">Translate complex technical analysis into clear narratives and actionable recommendations.</li>
</ul>

Delivery Excellence

<ul>
<li style="margin-left:0px;">Manage workflows with a focus on timely, accurate, and reproducible outputs.</li>
</ul>

<ul>
<li style="margin-left:0px;">Develop dashboards, maps, and user-friendly visualisations for decision-makers, including digital mapping and geoinformation-based visual analytics</li>
</ul>

<ul>
<li style="margin-left:0px;">Ensure strong documentation, version control, and reproducibility of geospatial methods.</li>
</ul>

<ul>
<li style="margin-left:0px;">Track overall project progress, flag risks, and ensure delivery meets stakeholder expectations.</li>
</ul>

Stakeholder Engagement

<ul>
<li style="margin-left:0px;">Support collaboration with research institutions, government partners, and technical agencies to ensure relevance and adoption of geospatial insights.</li>
</ul>

<ul>
<li style="margin-left:0px;">Build rapport with stakeholders through regular engagement and professional credibility.</li>
</ul>

<ul>
<li style="margin-left:0px;">Communicate findings clearly, tailoring outputs for non-technical audiences, including policymakers and program managers.</li>
</ul>

<ul>
<li style="margin-left:0px;">Contribute to knowledge products (whitepapers, case studies, technical notes) to share insights, particularly around sustainable development.</li>
</ul>

Capacity Building

<ul>
<li style="margin-left:0px;">Mentor internal teams on geospatial tools, AI/ML applications, and open-source workflows.</li>
</ul>

<ul>
<li style="margin-left:0px;">Conduct internal training sessions to strengthen applied skills and knowledge.</li>
</ul>

<ul>
<li>Foster collaboration and peer learning within the team.</li>
</ul>

<ul>
<li style="margin-left:0px;">Contributing to Organisational Knowledge Pool</li>
</ul>

<ul>
<li style="margin-left:0px;">Keep up-to-date with advances in geospatial science, AI/ML applications, and open-source technologies.</li>
</ul>

<ul>
<li style="margin-left:0px;">Share insights internally and contribute to discussions on geospatial applications for development.</li>
</ul>

<ul>
<li style="margin-left:0px;">Support the organisation in strengthening its expertise and credibility in applied geospatial analytics for social impact.</li>
</ul>

The Ideal Candidate:

<ul>
<li style="margin-left:0px;">Bachelor’s/Master’s/PhD in Econometrics/Statistics, Economics, Geoinformatics, Spatial Data Science, Computer Science, Environmental Science, or related fields.</li>
</ul>

<ul>
<li style="margin-left:0px;">3-5 years of professional experience in Data Science/Analytics</li>
</ul>

<ul>
<li style="margin-left:0px;">Proven track record of integrating geospatial and socio-economic data for policy/research/programmatic outcomes.</li>
</ul>

<ul>
<li style="margin-left:0px;">Proficiency in geospatial tools and libraries (QGIS, ArcGIS, GDAL, Rasterio, Geopandas, Shapely) and geostatistical and spatial analytical methods, will be a plus</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong programming skills in Python and/or R with hands-on experience in deep learning frameworks and data science pipelines</li>
</ul>

<ul>
<li style="margin-left:0px;">Publications or equivalent applied research outputs are desirable, especially in domains linking geospatial science, climate change, and socio-economic development.</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong analytical and research orientation with methodological rigour.</li>
</ul>

<ul>
<li style="margin-left:0px;">Ability to simplify technical concepts for diverse audiences.</li>
</ul>

<ul>
<li style="margin-left:0px;">Excellent collaboration, facilitation, and mentoring abilities.</li>
</ul>

<ul>
<li style="margin-left:0px;">Strong execution bias, adaptability, and a continuous learning mindset. </li>
</ul>

Data Science in Indore (UID-14835)

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