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Formulation Scientist Manager Jobs in Rochester, MI

Varsity Tutors

Data Science Tutor

Detroit, MI · Remote

$18 - $40/hr

Skilled at teaching the full data science workflow from question formulation through insight ... product management, marketing analytics, and healthcare informatics. * Curriculum Awareness ...

Amazon

Product Mgr III - Tech - AMZ9442569

Detroit, MI · On-site

$161K - $204K/yr

Develop and interpret information to assist management with decision-making, policy formulation ... Master's degree or foreign equivalent degree in Computer Science, Engineering, Business ...

Varsity Tutors

Business Analytics Tutor

Detroit, MI · Remote

$18 - $40/hr

... driven management positions. * Conceptual Teaching & Problem-Solving: Skilled at breaking down ... optimization problem formulation. Guides students through cleaning and preparing data sets ...

All JobsFormulation Scientist Manager JobsFormulation Scientist Manager Jobs in Rochester, MI

Formulation Scientist Manager information

See Rochester, MI salary details

$18

$34

$66

How much do formulation scientist manager jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for formulation scientist manager in Rochester, MI is $34.62, according to ZipRecruiter salary data. Most workers in this role earn between $23.22 and $40.05 per hour, depending on experience, location, and employer.

What are Formulation Scientist Managers?

Formulation Scientist Managers are professionals who oversee the development and optimization of product formulations, often in industries such as pharmaceuticals, cosmetics, or food. They lead teams of scientists to design, test, and improve formulas to ensure product stability, efficacy, and safety. In addition to technical expertise, they manage project timelines, resources, and regulatory compliance, serving as a bridge between research, manufacturing, and quality control teams. Their work is essential for bringing new and improved products to market efficiently and safely.

What are some common challenges faced by a Formulation Scientist Manager when leading a team?

As a Formulation Scientist Manager, one of the main challenges is balancing project deadlines with the need for thorough research and testing. Managing a diverse team of scientists requires strong communication skills to ensure everyone is aligned on project goals and methodologies. Additionally, staying updated on regulatory requirements and integrating new technologies into existing workflows can be demanding. Building a collaborative environment while fostering individual growth is key to overcoming these challenges and driving innovation.

What are the key skills and qualifications needed to thrive as a Formulation Scientist Manager, and why are they important?

To thrive as a Formulation Scientist Manager, you need deep expertise in chemistry, pharmaceutical sciences, or a related field, often supported by an advanced degree and significant industry experience. Familiarity with analytical instrumentation, formulation software, and regulatory standards like GMP is crucial for managing laboratory and compliance requirements. Strong leadership, project management, and cross-functional communication skills set standout managers apart in overseeing teams and complex projects. These competencies ensure the development of safe, effective products while meeting quality and regulatory expectations in a competitive industry.
What job categories do people searching Formulation Scientist Manager jobs in Rochester, MI look for? The top searched job categories for Formulation Scientist Manager jobs in Rochester, MI are:
What cities near Rochester, MI are hiring for Formulation Scientist Manager jobs? Cities near Rochester, MI with the most Formulation Scientist Manager job openings:
Formulation Scientist Manager jobs near you
Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

Sr. Staff Data Scientist - Machine Learning & AI (Quality, Vehicle & Engineering Analytics)

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 9 days ago

Stellantis rating

7.4

Company rating: 7.4 out of 10

Based on 124 frontline employees who took The Breakroom Quiz

17th of 44 rated automakers

Job description

About the Role:
We are looking for a Senior Staff Data Scientist (ML/AI) to serve as a technical leader, architect, and individual contributor within the Machine Learning & AI Engineering team at Stellantis.
This role sits at the intersection of machine learning, advanced analytics, experimentation, and large-scale vehicle/IoT data systems. You will define and influence how ML and AI are used across vehicle quality, engineering systems, and customer experience outcomes.
This is a high-impact, senior IC role (Staff/Principal level influence) responsible for shaping technical strategy, designing scalable ML systems, and driving measurable business outcomes such as quality improvement, warranty reduction, and customer experience enhancement.
What You Will Do:
Technical Leadership & ML Strategy (Staff-Level Ownership)
  • Define and evolve the ML/AI architecture and framework supporting quality, engineering, and vehicle analytics across the organization
  • Set technical direction for:
    • Machine learning systems
    • Experimentation platforms
    • Data science architecture
  • Act as a trusted technical advisor to senior leadership on:
    • Model feasibility
    • Trade-offs (accuracy, scalability, cost, interpretability)
    • Business impact of ML/AI initiatives
  • Influence roadmap decisions across engineering and product organizations

Advanced Machine Learning & Statistical Modeling
  • Develop and deploy predictive, prescriptive, and causal models using:
    • Vehicle data
    • IoT sensor data
    • Enterprise datasets
  • Apply advanced techniques including:
    • Statistical modeling
    • Machine learning algorithms
    • Deep learning / neural networks
  • Lead root cause analysis for vehicle quality, performance, and system failures
  • Design and build LLM-based systems and agentic AI solutions for engineering and quality use cases

Data Science Platform & Scalable Systems
  • Architect and guide development of large-scale distributed data and ML systems
  • Build and scale analytics pipelines using Spark-based distributed processing frameworks
  • Lead ML model lifecycle management, including:
    • Training
    • Validation
    • Deployment
    • Monitoring in production
  • Ensure models and systems are:
    • Explainable
    • Reliable
    • Production-ready
    • Compliant with automotive/regulatory standards

Experimentation & Product Impact
  • Own and evolve the experimentation framework/platform for safe, scalable testing of vehicle and software features
  • Design statistically sound experiments (A/B tests and beyond)
  • Translate experimental results into clear product and engineering decisions
  • Drive measurable business outcomes including:
    • Warranty cost reduction
    • Improved product quality
    • Enhanced customer experience
    • Revenue-impacting insights

Influence, Mentorship & Knowledge Sharing
  • Mentor senior and mid-level data scientists, raising technical standards across the team
  • Help teams with:
    • Problem formulation
    • Research design
    • Statistical interpretation
  • Contribute to internal knowledge systems and external-facing technical content (e.g., blogs or papers)
  • Serve as a cross-functional leader bridging engineering, product, and executive teams

What Success Looks Like (Top Performers)
Strong candidates will demonstrate:
  • Proven impact from deployed ML systems or production analytics products
  • Quantifiable improvements in:
    • Vehicle quality
    • Warranty reduction
    • Customer experience metrics
  • Ability to influence technical strategy beyond their immediate team
  • Strong communication skills with executive and non-technical stakeholders

Demonstrated ability to turn complex analysis into business decisions and outcomes
Basic Qualifications:
  • Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • A minimum of 8 years of experience in data science, advanced analytics, or machine learning, including a minimum of 5 years of hands-on experience with Databricks, Palantir, Snowflake, or AWS SageMaker
  • Expert-level proficiency in:
    • Python (or R)
    • SQL
  • Strong foundation in:
    • Machine learning algorithms
    • Statistical modeling
    • Neural networks / deep learning
  • Experience building ML solutions on distributed systems (e.g., Spark)

Preferred Qualifications:
  • Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field
  • Experience with:
    • Large Language Models (LLMs)
    • Fine-tuning foundation models
    • Agentic AI systems
  • Experience building ML solutions in engineering, automotive, propulsion, or battery systems
  • Strong understanding of vehicle quality (QA), reliability, or manufacturing analytics
  • Experience working in high-scale enterprise or regulated environments

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