Data Scientist developing and implementing LLM - based agents and leveraging AI techniques to improve client value. Collaborating on project challenges in a dynamic, start - up environment at Gartner.
About the role
- Lead Data Scientist providing data science expertise and technical leadership for Caterpillar aftermarket parts forecasting. Managing complex analytics processes and ensuring accurate insights generation for critical business decisions.
Responsibilities
- Provide specialized data science expertise and technical leadership to support all aspects of forecast analytics for Caterpillar aftermarket parts and related special projects.
- Manage and optimize key analytical processes that support the enterprise-critical Dealer Parts Orders (DPO) forecast and insights generation.
- Oversee the end-to-end Parts Long-Term Forecast (LTF) process – spanning system architecture design and implementation; data engineering and statistical model development; user training, and stakeholder approvals.
- Ensure accurate and efficient forecasting.
- Safeguard the integrity of both the Sales & Operations Planning (S&OP) forecast disaggregation and the annual business plan disaggregation for DPO.
- Own the statistical modeling required to calculate probabilistic confidence intervals for aftermarket parts forecasts.
- Ensure timely, accurate updates to DPO systems and provide expert-level support for all product-based allocation inquiries.
- Set priorities and prepare work plans to complete broadly defined assignments and achieve desired results.
- Responsible for Value Stream Mapping for Business Process analysis and improvement.
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 a wide range of industry problems.
- 5+ years of extensive experience in applying statistical tools and techniques for time series analysis and modelling; demonstrating a 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 applications 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
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