Product Analyst for a leading media tech company managing SEO - friendly content and commercial campaigns. Collaborate with teams for digital content production and user engagement analysis.
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
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Scientist at Capital One leveraging machine learning models for credit underwriting decisions. Partnering with data scientists, engineers, and product managers using advanced technologies.
Data Scientist Analyst at BBVA transforming complex data into strategic solutions using machine learning. Collaborating within Banking Ops team to improve operational efficiency and customer experience.
Data Scientist leading key analytical projects at BBVA AI Factory in Madrid. Collaborate with multidisciplinary teams to drive data - driven solutions for banking processes.
Senior Data Scientist focusing on developing generative AI solutions for financial applications at BBVA. Involved in evaluating models, developing analytical solutions, and iterative experimentation processes.
Data Scientist specialized in Machine Learning and Generative AI at BBVA AI Factory. Collaborating with experts to deliver innovative AI solutions for the banking industry.
Data Scientist at BBVA AI Factory focusing on AI solutions in finance. Collaborate to develop AI - driven customer relationship models and analytics to enhance banking processes.
Data Assessor employing machine learning methods to enhance business relationships. Focused on deriving insights and applying data science principles to improve user experience.
Data Science Specialist leading predictive modeling initiatives to support product innovation at Nestlé Nutrition. Collaborating with cross - functional teams to translate complex data into actionable insights.
BI & Visualization Developer at Conduent working on advanced visualizations and supporting analytics solutions. Collaborating with cross - functional teams and mentoring associates in a hybrid environment.