Senior Manager, Data Engineering & Applied Data Science

Thermo Fisher

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Carlsbad, CAFrederick, MDPittsburgh, PA
Salary
$152,000–$227,900 / yr
Employment
Full-time
Posted
6 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $191k
This role $190k
$141k $239k
below market most similar roles pay here above market

This role pays less than 53% of similar roles. Most pay $152,025–$229,775 — the blue band above. At the midpoint, this role pays about $190k versus about $191k for comparable roles.

Based on 240 similar postings.

Employer

About Thermo Fisher

Thermo Fisher Scientific is the world leader in serving science, providing analytical instruments, equipment, reagents, consumables, software, and services for life sciences research, pharmaceutical manufacturing, and diagnostics. Industry: Life Sciences & Laboratory Equipment

Thermo Fisher currently has 14 open roles on FindRole.

Listed pay typically runs $107,500–$165,000 across 6 roles with salary data.

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View all roles at Thermo Fisher

At a glance

TL;DR · Senior Manager, Data Engineering & Applied Data Science

The Sr. Manager, Data Engineering & Applied Data Science leads a multidisciplinary team responsible for the strategy, design, and delivery of enterprise data products and AI solutions. This role involves transforming business challenges into scalable, production-ready data foundations and advanced analytics. Key responsibilities include leading the delivery of machine learning and Generative AI solutions, establishing engineering standards for DataOps, CI/CD, and automation, and ensuring data is governed and optimized for analytics. The successful candidate will utilize Python, R, and SQL alongside frameworks like TensorFlow, PyTorch, and scikit-learn. They must also leverage cloud platforms such as AWS, Azure, or GCP, and visualization tools like Tableau and Power BI to solve complex technical problems and drive digital transformation through data-driven insights.

What you'll do

  • Translate business priorities into scalable enterprise data products, machine learning, and AI solutions.
  • Lead the design and delivery of secure, scalable data pipelines and DataOps engineering standards.
  • Guide the production deployment of Generative AI, machine learning models, and reusable analytics frameworks.
  • Ensure enterprise data is governed, contextualized, and optimized for AI and analytics use cases.
  • Develop technology roadmaps and evaluate emerging architectural patterns to accelerate AI adoption.
  • Build and mentor high-performing multidisciplinary teams of data engineers and data scientists.
  • Partner with security, architecture, and platform functions to align priorities and drive execution.

What we're looking for

  • Advanced Degree plus 6 years of experience, or Bachelor's Degree plus 8 years of experience in data science and analytics leadership roles.
  • Preferred fields of study include Data Science, Computer Science, Statistics, Mathematics, Analytics, or related fields (preferred).
  • Advanced certifications in data science, machine learning, or AI technologies are valued (preferred).
  • Strong expertise in machine learning, AI, statistical modeling, and implementing large-scale data science solutions.
  • Advanced proficiency in Python, R, and SQL, with experience in major AI/ML frameworks like TensorFlow, PyTorch, and scikit-learn.
  • Experience with cloud platforms (AWS, Azure, GCP), big data technologies, and data visualization tools like Tableau or Power BI.
  • Demonstrated success leading and mentoring data science teams using Agile/Scrum methodologies.
  • Strong knowledge of data governance, regulatory compliance, and cross-functional project management.

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