Sr. Manager, Data Engineering & Applied Data Science

Thermo Fisher Scientific Inc.
Carlsbad, CA, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
8 years minimum
Compensation
$152,000.0 - $227,900.0
Working hours
Regular working hours
Job source

Tech stack

Training Data Artificial Intelligence Amazon Web Services Data Analysis Application Frameworks Architectural Patterns Microsoft Azure Big Data Cloud Computing Continuous Integration Information Engineering Data Governance
+17 more
Data Visualization R (Programming Language) Python (Programming Language) Machine Learning Scrum Methodology Power BI Tensorflow DataOps Software Deployment SQL Databases Tableau (Software) Google Cloud Pytorch Generative AI Scikit Learn Information Technology Data Pipelines

Job description

The Senior Manager - Data Engineering & Applied Data Science is responsible for leading the strategy, design, and delivery of enterprise data products, applied data science, and AI solutions that enable business growth and digital transformation. This role leads a multidisciplinary team responsible for Data Engineering and Applied Data Science, transforming business challenges into scalable, production-ready data and AI products.

The successful candidate combines strong technical leadership with business acumen to design data products that address business needs, build AI-ready data foundations, develop advanced analytics and machine learning solutions, and continuously evolve capabilities through the adoption of emerging technologies and engineering best practices. This role is also accountable for ensuring enterprise data is AI-ready-standardized, contextualized, governed, and optimized for analytics, machine learning, and Generative AI use cases. * Lead Data & AI Solution Delivery - Translate business priorities into scalable enterprise data products, advanced analytics, machine learning, and AI solutions that deliver measurable business value.

  • Drive Data Engineering Excellence - Lead the design and delivery of reliable, secure, and scalable data pipelines and products while establishing engineering standards across DataOps, CI/CD, automation, observability, and cloud-native development.
  • Advance Applied Data Science & AI - Guide the development and production deployment of machine learning, Generative AI, and advanced analytics solutions, including reusable frameworks and scalable AI capabilities.
  • Build AI-Ready Data Foundations - Ensure enterprise data products are trusted, governed, contextualized, and optimized for analytics and AI through strong data quality, metadata, lineage, semantic models, and accessibility.
  • Shape Technology Strategy & Innovation - Develop technology roadmaps and evaluate emerging technologies and architectural patterns that accelerate AI adoption, improve engineering productivity, and strengthen enterprise data capabilities.
  • Lead Teams & Strategic Partnerships - Build and develop high-performing Data Engineering and Applied Data Science teams while partnering across business, architecture, platform, security, and technology functions to align priorities, communicate outcomes, and drive execution.

Requirements

  • 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: Data Science, Computer Science, Statistics, Mathematics, Analytics, or related field
  • Advanced certifications in data science, machine learning, or AI technologies are valued
  • Strong expertise in machine learning, AI, and statistical modeling techniques
  • Advanced proficiency in programming languages including Python, R, and SQL
  • Experience with major AI/ML frameworks (TensorFlow, PyTorch, scikit-learn)
  • Demonstrated success leading and mentoring data science teams
  • Expertise in data visualization tools (Tableau, Power BI) and BI platforms
  • Proven track record of implementing large-scale data science solutions
  • Experience with cloud platforms (AWS, Azure, GCP) and big data technologies
  • Strong knowledge of data governance and regulatory compliance
  • Excellent project management and cross-functional collaboration skills
  • Outstanding communication abilities to translate technical concepts for diverse audiences
  • Experience with Agile/Scrum methodologies
  • Ability to travel up to 20% as needed
  • Proven ability to deliver business results through data-driven insights
  • Experience with automation tools and process optimization
  • Strong problem-solving and analytical thinking capabilities

Benefits & conditions

The salary range estimated for this position based in California is $152,000.00-$227,900.00.

This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:

  • A choice of national medical and dental plans, and a national vision plan, including health incentive programs
  • Employee assistance and family support programs, including commuter benefits and tuition reimbursement
  • At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
  • Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
  • Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount

About the company

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.

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