Senior Data Scientist

Job Summary

We are looking for a Data Scientist with 5+ years of overall professional experience to develop scalable, data-driven solutions focused on time-series forecasting, predictive analytics, and advanced data manipulation. The ideal candidate will have strong hands-on experience with Python, pandas, NumPy, Matplotlib, PySpark, Databricks, Git, and Azure DevOps, along with a solid understanding of statistical modeling and data analysis principles.

Required qualifications

• Develop, evaluate, and deploy time-series forecasting models for business and commercial applications.
• Build predictive analytics solutions to support data-driven decision-making.
• Perform data preparation, cleansing, transformation, and feature engineering using Python and pandas.
• Work with large datasets using PySpark and optimize data processing workflows.
• Develop and maintain data pipelines and analytical workflows in Databricks.
• Analyze trends, seasonality, outliers, and other patterns in historical data.
• Select appropriate forecasting and predictive modeling techniques based on business requirements.
• Validate model performance using relevant statistical and business metrics.
• Collaborate with business stakeholders, data engineers, and technology teams to translate business problems into analytical solutions.
• Use Azure DevOps for source control, work-item tracking, CI/CD, and collaborative development.
• Document analytical methodologies, assumptions, code, and model results clearly.
• Monitor model performance and recommend improvements when data or business conditions change.
• Follow established standards for code quality, testing, version control, and deployment.

Required Qualification & Skills:

• Bachelor’s or master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• Strong programming skills in Python, with 5+ years of relevant professional experience.
• Advanced proficiency in pandas, including data cleansing, reshaping, merging, aggregation, group-based operations, and efficient manipulation of large datasets.
• Strong working knowledge of NumPy for numerical computing, array operations, and efficient data processing.
• Experience using Matplotlib to create clear and insightful visualizations for exploratory analysis and model evaluation.
• Practical experience with time-series forecasting techniques, including trend and seasonality analysis, lag features, rolling statistics, and forecast evaluation.
• Strong understanding of predictive analytics, statistical analysis, and model validation.
• Hands-on experience with PySpark for distributed data processing.
• Experience working with Databricks notebooks, jobs, clusters, and data workflows.
• Familiarity with SQL for data extraction, joining, aggregation, and analysis.
• Experience using Git for source control, branching, merging, pull requests, and collaborative development.
• Experience using Azure DevOps for version control, task management, CI/CD processes, and release coordination.
• Working knowledge of Linux operating systems and familiarity with the command line.
• Understanding of data quality, reproducibility, and documentation best practices.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience applying forecasting and predictive analytics to sales, demand, pricing, revenue, or other commercial datasets.
• Familiarity with Azure data and analytics services.
• Experience with data visualization tools such as Power BI or similar platforms.
• Knowledge of model monitoring, performance tracking, and production support practices.
• Experience optimizing Python, pandas, SQL, or PySpark code for performance and scalability.
• Familiarity with Agile delivery practices and collaborative software development.

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