Rackera - Durham, NC

posted 5 months ago

Full-time - Senior
Durham, NC

About the position

We are looking for a passionate Data Scientist to join our team and help us build the future of forecasting and business planning. In this role, you will be responsible for developing and deploying forecasting models using a variety of techniques, including machine learning, statistics, and data mining. You will be contributing to the codebase of our forecasting engine, which combines data signals and drivers from multiple sources to generate forecasts for various business units. Your work will be pivotal in driving the transformation of our forecasting capabilities by embedding predictive analytics and data science into global decision-making processes, empowering business units with scalable and reusable models. As a Senior Data Scientist, you will also be responsible for designing and implementing data pipelines to collect, clean, and prepare data for forecasting models. This role requires a deep understanding of machine learning models and engineering, advanced statistics, and time series forecasting. You will oversee the ML Ops from a model standpoint, managing data and model drift, retraining models regularly, and upgrading models and associated technical pipelines as necessary. Collaboration with cross-functional stakeholders and subject matter experts throughout the product solution lifecycle is essential to ensure that requirements are met and solutions are fully integrated into business processes to deliver value. This position reports to the Associate Director of Enterprise Analytics and is a long-term contract role based in Durham, NC, with a hybrid work model requiring three days per week onsite. The ideal candidate will have a strong enterprise background, polished communication skills, and the ability to work effectively in a team-oriented environment.

Responsibilities

  • Develop and deploy forecasting models using machine learning, statistics, and data mining techniques.
  • Contribute to the codebase of the forecasting engine that generates forecasts for multiple business units.
  • Design and implement data pipelines to collect, clean, and prepare data for forecasting models.
  • Drive the transformation of forecasting capabilities by embedding predictive analytics into global decision-making processes.
  • Oversee ML Ops from a model standpoint, managing data and model drift.
  • Retrain models regularly and upgrade models and technical pipelines as necessary.
  • Collaborate with cross-functional stakeholders throughout the product solution lifecycle to ensure requirements are met and solutions are integrated into business processes.

Requirements

  • Bachelor's degree in Computer Science, Statistics, Data Science, Applied Mathematics, or related quantitative disciplines (Master's degree preferred).
  • 7+ years of overall data science and machine learning experience.
  • 5+ years of business experience in a data science or machine learning role in the industry.
  • Deep understanding of ML models and ML engineering, advanced statistics, and time series forecasting.
  • Proficiency in Python (required), Scala, Java, C++, and SQL.
  • Experience with big data frameworks like Spark is an asset.
  • Experience with building, deploying, and maintaining industrialized data pipelines.
  • Experience with standard SDLC process and DevOps including version-control (GitHub/SVN) and CI/CD.
  • Experience in Azure and Databricks (or other cloud equivalents).
  • Strong project management skills to stay on top of timelines and deliverables.

Nice-to-haves

  • Knowledge of design and architecture principles is a plus.
  • Experience with navigating and delivering production-grade code in large, complex industrialized code bases.
  • Autonomy and creativity in designing technical solutions to solve business problems.
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