Job Description:
Strong Data Science + ML Engineer with 7+ years of experience in traditional machine learning and statistical modeling. The candidate should have strong expertise in time series analysis, clustering, predictive analytics, forecasting, regression, classification, feature engineering, and model selection.
The role requires hands-on capability to frame business problems, choose the right algorithms, build and validate models, and work with stakeholders to deliver scalable and actionable insights.
Must Have skills:
- 7+ years in Data Science / ML / Advanced Analytics
- Strong hands on experience in time series, forecasting, clustering, predictive modeling
- Strong understanding of algorithm selection and model evaluation
- High Proficiency in Python, SQL, pandas, numpy, scikit-learn, etc
- Strong Experience in data wrangling, feature engineering, and model tuning
- Strong stakeholder communication and problem-solving skills
- Strong GCP skills
Preferred Skills:
- Highly preferred to have any geospatial experience (doesn?t matter the tool). There is going to be a good amount of geospatial based analysis in this scope of work, so Experience with spatial data such as polygons and points is sufficient.
- Experience in Churn analysis or use cases like that
- Telecom / enterprise analytics background
Roles and Responsibilities
- Develop and maintain geospatial data pipelines, spatial analyses, and mapping solutions to support business decision?making.
- Build predictive forecasting models using statistical and machine?learning techniques to estimate demand, workloads, or business KPIs.
- Design and optimize customer churn models, identifying key drivers and creating actionable insights to reduce churn.
- Collaborate with cross?functional teams to translate analytical findings into strategic recommendations.
- Ensure data accuracy, model performance, and continuous improvement through periodic validation and refinement.
- Present complex analytical outputs through clear dashboards, visualizations, and stakeholder?friendly reports.
- Mentor junior analysts and contribute to best practices in analytics, modeling, and geospatial methodologies.