Lead Data Scientist

Role Overview

• Responsible for answering questions regarding the Dealer Parts Orders (DPO) product-based allocation.
• Own the Parts LTF process: system architecture design, analytics solution development, and user training.
• Own the design, development and maintenance of PowerBI dashboards to deliver the forecast analytics solutions.
• Responsible for the integrity of the disaggregation of the S&OP forecast.
• Own the foundational research in leveraging Gen AI LLM models for explainable forecast initiative.
• Lead design and implementation of LLM-powered analytics insight generation to explain forecast miss.
• Own the statistical modelling for calculating forecast confidence intervals for aftermarket parts.
• Responsible for the integrity of the annual business plan disaggregation for DPO.
• Regularly and accurately maintain and update DPO systems and answer all related queries for their assigned allocations.
• Responsible for setting priorities and preparing work plan to complete broadly defined assignments and achieve desired results.
• Responsible for Value Stream Mapping for Business Process analysis and improvement.
• Responsible for Impact key quality goals including Customer Satisfaction, Continuous Improvement, Timeliness, Accuracy, Efficiency, Cost Savings, Process Quality, etc.

Requirements

• Doctoral or Master’s degree with 5 years of experience or a Bachelor’s degree with 10 years of experience in Computer Science, Mathematics, Engineering, Accounting, Statistics, Data Science, Business Analytics, or a closely related field with extensive coursework in mathematical and statistical modeling.
• 5+ years of extensive experience in applying statistical models and methods to solve wide range of industry problems.
• 5+ years of extensive experience in applying statistical tools and techniques for time series analysis and modelling; demonstrating deep understanding of fundamental concepts of time series analysis: stationarity; seasonality; time series decomposition.
• 5+ years of extensive experience in developing end-to-end analytics solutions that span from data pipeline to insights delivery.
• Deep expertise and experience in applying classical statistical modelling methods, tools and techniques for time series forecasting included in the GLM, ARIMA and State Space family of models.
• Deep expertise and experience in contemporary deep learning tools and techniques for time series forecasting included in Transformer family of models with self-attention mechanism.
• Deep understanding of models and methods for Hierarchical time series and forecast reconciliation.
• Extensive experience and proficiency in R, Python and SQL / Snowflake queries
• Experience with AWS Cloud platform and AWS Glue
• Experience with Alteryx and SAS
• Extensive experience with PowerBI for development of reporting dashboards
• Experience with Rshiny / Dash / Streamlit for development of interactive web application for forecast analytics.
• High level of interpersonal skills and excellent communication and storytelling skills
• Experience in Value Stream Mapping for Business Process analysis and improvement.

Tech Stack

• AWS
• Cloud
• Python
• SQL

Benefits

• Medical, dental, and vision benefits*
• Paid time off plan (Vacation, Holidays, Volunteer, etc.)*
• 401(k) savings plans*
• Health Savings Account (HSA)*
• Flexible Spending Accounts (FSAs)*
• Health Lifestyle Programs*
• Employee Assistance Program*
• Voluntary Benefits and Employee Discounts*
• Career Development*
• Incentive bonus*
• Disability benefits
• Life Insurance
• Parental leave
• Adoption benefits
• Tuition Reimbursement