Senior Data Scientist
3 weeks ago
Job Description
• Deliver end-to-end ML and data science solutions from idea conception through planning, requirements, design, development, testing, production, and deployment/business process integration.
• Do first line and second line model and modeling code base maintenance, incl. advanced debugging whenever necessary; coordinate with engineers for specialized back-end and UI upgrades / debugging.
• 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.
• 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.
Key Skills and Abilities
• Deep understanding of and experience with ML models and ML engineering, advanced statistics, time series forecasting, best practice application of data science in a business context (e.g., back-testing & piloting), model architecture, and use cases.
• Proficiency in Python (required) / Scala / Java / C++ and SQL. Knowledge of big data frameworks like Spark is an asset.
• Experience with navigating, collaborating on, and delivering production-grade code in large, complex industrialized code bases.
• 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)
• Autonomy and creativity with an ability to design suitable technical solutions to solve business problems.
• Understanding of design and architecture principles is a plus.
• Experience in data management, e.g., wrangling, extraction, normalization.
• Strong project management skills to stay on top of the timelines and deliverables.
Requirements:
Education And Experience Required
• Bachelor's degree in Computer Science, Statistics, Data Science, Applied Mathematics, or related quantitative disciplines (Master's degree preferred).
• 5+ years of overall data science and machine learning experience.
• 3+ years business experience in a data science or machine learning role in the industry (must have demonstrated working with business units).
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