This is a temporary role through Magnit Global with a global manufacturer. This is a 6-month contract role. This is a hybrid role to Pleasanton, CA, working 2-3 days a week onsite.
Summary: Sr Data Scientist – Forecasting and ML Ops
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 also be responsible for designing and implementing data pipelines to collect, clean, and prepare data for forecasting models. Forecasting team would drive this transformation through embedding predictive analytics and data science capabilities into the global decisions, empowering business units with scalable, reusable models. This position reports to Associate Director, Enterprise Analytics.
Job Description
· Deliver end-to-end analytics and data science solutions from idea conception through planning, requirements, design, development, testing, production, and deployment/business process integration
· Oversee the solution's ML Ops from a model standpoint, own the management of data & model drift.
· Retrain the models regularly, upgrade the models and associated technical pipelines, such as addition of signals or adaptation of the models to a change in input source / format.
· Do first line and second line model maintenance incl. advanced debugging whenever necessary; coordinate with engineers for specialized back end and UI upgrades / debugging.
· Collaborate with cross-functional stakeholders/SMEs throughout product solution lifecycle to ensure requirements are met and solutions are fully integrated in business processes to deliver value.
· Evaluate existing and new data science tools and techniques, lead the development of data science best practices across the enterprise.
Key Skills and Abilities
· Deep understanding and experience with ML models and ML engineering, advanced statistics, time series forecasting, machine-learning models, best practice application of data science in a business context (e.g., back-testing & piloting), model architecture, and use cases.
· Experience in data management, e.g., wrangling, extraction, normalization
· Experience with building, deploying, and maintaining industrialized data pipelines is required.
· Knowledge of big data framework like Spark is an asset.
· Ability to navigate, collaborate and deliver production-grade code in a complex industrialized code base.
· Experience with standard SDLC process and DevOps including version-control (GitHub/SVN) and CI/CD.
· Experience using business intelligence tools like Power BI / Tableau
· Experience in Azure and Databricks are required as well.
· Understanding of design and architecture principles is a plus.
· Good communication and presentation skills: ability to synthesize, simplify, and explain complex problems to different audiences across functions and levels; ability to convey insight through storytelling.
· Strong project management skills to stay on top of the timelines and deliverables.
· Autonomy and creativity with an ability to design suitable technical solutions to solve business problems.
Education And Experience Required
· Bachelor's degree in Statistics, Data Science, Applied Mathematics, Computer Science, Business Analytics, or related quantitative disciplines (Master's degree preferred)
· 5+ years of overall data science experience
· 3+ years business experience in a Data Science or Advanced Analytics role in the industry (must have demonstrated working with business units)
Hourly Pay Rate Range (dependent on location, experience, expectation)
