Senior Data and Applied Scientist-Forecasting

Job Description:

• Design, build, and maintain predictive machine learning and statistical models to optimize solutions across Pattern.
• Research, experiment, and present novel forecasting approaches.
• Communicate potential model improvements, data needs, and opportunities across relevant business units and developer teams.
• Continuously optimize the quality of our machine learning models, especially for key forecasting metrics like bias and WAPE.
• Conduct research to integrate new data sources, innovate in feature engineering, fine-tune algorithms, and enhance data pipelines for robust model performance.
• Analyze large datasets to extract actionable insights that guide business decisions.
• Work closely with data science teams across different regions (US and India), ensuring seamless collaboration and knowledge sharing.
• Follow code standards and best practices.
• Perform root cause analysis to determine accuracy defects to drive improvements.

• Bachelor's or Master's in Data Science, Computer Science, Statistics, Economics, or a related field.
• 2-6 years of industry experience in building and deploying machine learning solutions.
• 1-3 years of industry experience in demand forecasting or complex forecasting scenarios.
• Excellent communication (written and verbal) across departments with different levels of machine learning knowledge
• Strong data manipulation and programming skills in Python and SQL and hands-on experience with libraries such as Pandas, Numpy, Scikit-Learn, XGBoost.
• Strong problem-solving skills and an ability to analyze complex data.
• In depth expertise in a range of machine learning and statistical techniques such as linear and tree-based models along with understanding of model evaluation metrics.
• Experience with Git, AWS, and deep learning models is advantageous.

Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.