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