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Senior Data Scientist/Engineer
Senior Data Scientist/EngineerThermo Fisher Scientific • Raleigh, North Carolina, United States of America
Senior Data Scientist / Engineer

Senior Data Scientist / Engineer

Thermo Fisher Scientific • Raleigh, North Carolina, United States of America
[job_card.variable_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

Lead the architecture and implementation of data pipelines and Microsoft Fabric-based data models to enable unified financial reporting and analytics.

  • Build, review, and optimize ETL processes developed in Python, ensuring efficient data ingestion, transformation, and quality across diverse data sources (ERP, financial systems, operational platforms).
  • Partner with Finance leadership to define business requirements, translate them into robust technical builds, and deliver actionable insights for decision-making.
  • Establish and implement data engineering standards, including coding guidelines, documentation, version control, and automated testing for ETL pipelines.
  • Develop, test, and deploy scalable data models using Lakehouse architectures and Fabric Data Warehouses to support forecasting, planning, and profitability analysis.
  • Provide technical leadership and mentorship to data engineers and analysts, encouraging skill development in Fabric, Power BI, and modern Python data frameworks (Pandas, PySpark, SQLAlchemy).
  • Collaborate multi-functionally with Finance, IT, and Data Governance teams to ensure alignment with enterprise data architecture and security policies.
  • Keep up to date with developments in Microsoft Fabric, Power BI, Python, and data orchestration tools, and suggest their strategic implementation.
  • Run multiple concurrent initiatives — leading all aspects of planning, prioritisation, communication, and customer engagement.

Requirements / Qualifications :

  • Bachelor’s degree or equivalent experience in a quantitative field, such as Statistics, Computer Science, Mathematics, Data Science or a related field, master’s or equivalent experience preferred
  • Proven experience in a data engineer or data science role with dynamic responsibilities and scope
  • Experience building models and analyzing large, complex data sets yielding opportunities for revenue and / or process improvement within an organization
  • Technical proficiency in Python and SQL
  • Proficiency in data engineering and reporting platforms (Databricks, Power Bi, Tableau, SAS Analytics)
  • Interpersonal skills : outstanding verbal / written communication
  • Proven track record of achieving desired results without direct report authority
  • Knowledge of Agile / Scrum methodology is a plus
  • Hands-on experience with distributed computational framework, such as Spark
  • Command of statistical topics, including distributions, hypothesis testing, and experiment building
  • Minimal travel required about 10%
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