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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

statistical modelingtime series analysisdata pipeline developmentforecast reconciliationGLMARIMAState Space modelsTransformer modelsRPython

Soft Skills

interpersonal skillscommunication skillsstorytelling skillsleadershiporganizational skills