Data Scientist

We are seeking an experienced Data Scientist with strong expertise in machine learning, predictive analytics, SQL, and data science methodologies. The role will focus on developing and validating predictive models, extracting actionable insights from complex datasets, and applying advanced analytics to solve business problems.

The ideal candidate will have hands-on experience with Python, machine learning, MLOps, large-scale data analysis, visualization, and GIS/data analytics.

• Develop, validate, and deploy machine learning and predictive models using Python.
• Apply supervised and unsupervised learning techniques to solve business and operational problems.
• Perform statistical analysis, data mining, feature engineering, and exploratory data analysis.
• Work with large and complex datasets using advanced SQL.
• Develop data-driven solutions for forecasting, optimization, customer analytics, and operational analytics.
• Create dashboards and visualizations using tools such as Power BI to communicate insights effectively.
• Apply GIS and spatial data analysis techniques where applicable.
• Support the end-to-end machine learning lifecycle, including model development, deployment, monitoring, and optimization.
• Apply MLOps practices, including model versioning, CI/CD, deployment, monitoring, and lifecycle management.
• Collaborate with business and technical stakeholders to translate analytical findings into actionable recommendations.
• Communicate complex technical concepts and model results clearly to both technical and non-technical audiences.

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline.
• 5+ years of experience in Data Science, Machine Learning, Predictive Analytics, or a related field.
• Strong hands-on experience developing and validating machine learning models using Python.
• Strong expertise in SQL and experience working with large datasets.
• Strong understanding of supervised and unsupervised learning techniques.
• Experience with statistical analysis, predictive modeling, data mining, and feature engineering.
• Experience developing predictive analytics solutions.
• Hands-on experience with MLOps and machine learning model lifecycle management.
• Experience with data visualization and reporting tools such as Power BI.
• Strong analytical, problem-solving, and communication skills.
• Ability to translate complex analytical results into clear business recommendations.
• Experience or background in GIS / geospatial data analytics.

• Master's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or another quantitative discipline.
• Experience with AWS, Azure, or other cloud platforms.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Experience with model deployment, monitoring, CI/CD pipelines, and automated ML workflows.
• Familiarity with forecasting, optimization, customer analytics, or operational analytics.
• Experience working with spatial datasets, geospatial analytics, or GIS platforms.