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Privacy Preserving Machine Learning Jobs in Detroit, MI

OneMagnify

Data Scientist

Detroit, MI · On-site

$120 - $170/hr

Use Databricks for large‑scale data processing and machine learning workflows. * Translate ... Adhere to data governance, privacy, and compliance standards across all work. What You'll Need * BA ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

... machine learning initiatives * Develop and optimize ETL/ELT processes to ingest, transform, and ... Follow established standards for data governance, security, privacy, and compliance * Monitor ...

Conclusive Marketing

Data Scientist

Detroit, MI · On-site

Use Databricks for large-scale data processing and machine learning workflows Translate ... Adhere to data governance, privacy, and compliance standards across all work What You'll Need * BA ...

OneMagnify

Data Scientist

Detroit, MI · On-site

Use Databricks for large-scale data processing and machine learning workflows Translate ... Adhere to data governance, privacy, and compliance standards across all work What You'll Need * BA ...

General Motors

Senior ML Compiler Engineer

Warren, MI · On-site

$98K - $134K/yr

... preserving correctness and robustness in realworld conditions. We partner closely withAI ... Experience developing and deploying machine learning models Compensation: The compensation ...

Guardian Alarm

Director, Data Strategy

Southfield, MI · On-site

... machine learning, and emerging business needs. This role also plays a critical part in Guardian ... Partner with IT and business stakeholders to ensure data security and privacy requirements are ...

Stellantis

Data Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

Follow established standards for data governance, security, privacy, and compliance * Monitor ... Experience with machine learning data preparation and feature engineering * Understanding of data ...

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All JobsPrivacy Preserving Machine Learning JobsPrivacy Preserving Machine Learning Jobs in Detroit, MI

Privacy Preserving Machine Learning information

See Detroit, MI salary details

$98.5K

$114.3K

$128.2K

How much do privacy preserving machine learning jobs pay per year?

As of Sep 2, 2026, the average yearly pay for privacy preserving machine learning in Detroit, MI is $114,346.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $127,700.00 per year, depending on experience, location, and employer.

What is privacy preserving machine learning?

Privacy preserving machine learning refers to techniques and methods that allow data analysis and model training while protecting sensitive information. This field focuses on ensuring that personal or confidential data is not exposed or compromised during the development and deployment of machine learning models. Approaches such as federated learning, differential privacy, and homomorphic encryption are commonly used. These methods enable organizations to leverage data for insights and predictions without violating privacy regulations or risking data breaches. Privacy preserving machine learning is especially important in industries like healthcare, finance, and any sector handling personal data.

What are the key skills and qualifications needed to thrive as a privacy preserving machine learning engineer?

To thrive as a Privacy Preserving Machine Learning Engineer, you need a strong background in machine learning, data privacy techniques (such as differential privacy or federated learning), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow Privacy, PySyft, and privacy-enhancing technologies, along with certifications in data security or privacy, are often required. Strong problem-solving abilities, meticulous attention to detail, and the ability to communicate complex technical concepts clearly set top professionals apart. These skills ensure the development of robust machine learning models that protect sensitive data while delivering valuable insights, maintaining compliance and trust.

What are some common challenges faced by professionals working in privacy preserving machine learning roles?

Professionals in Privacy Preserving Machine Learning often encounter challenges such as balancing model accuracy with strict privacy requirements, selecting appropriate privacy-preserving techniques (like differential privacy or federated learning), and ensuring compliance with evolving data protection regulations. Collaborative projects may also involve coordinating with legal, data security, and software engineering teams to implement robust solutions. Additionally, staying updated with the latest research and adapting to new threats or vulnerabilities is a continuous part of the role.

What is the difference between Privacy Preserving Machine Learning vs Data Scientist?

AspectPrivacy Preserving Machine LearningData Scientist
Required CredentialsTypically requires knowledge of machine learning, data privacy, and security certificationsRequires degrees in data science, statistics, or related fields; certifications like Certified Data Scientist are common
Work EnvironmentWorks in research, development, and implementation of privacy-focused ML models, often in tech or finance sectorsAnalyzes data, builds models, and provides insights across various industries including marketing, finance, and healthcare
Employer & Industry UsageUsed by organizations prioritizing data privacy, such as healthcare, finance, and tech companiesEmployed across diverse sectors for data analysis, predictive modeling, and decision support

Privacy Preserving Machine Learning focuses on developing models that protect data privacy during training and inference, while Data Scientists analyze and interpret data to generate insights. Both roles require strong analytical skills, but Privacy Preserving Machine Learning emphasizes security and privacy techniques, whereas Data Scientists focus on data analysis and modeling.

What are popular job titles related to Privacy Preserving Machine Learning jobs in Detroit, MI?

For Privacy Preserving Machine Learning jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Privacy Preserving Machine Learning jobs in Detroit, MI look for?

The top searched job categories for Privacy Preserving Machine Learning jobs in Detroit, MI are:

Privacy Preserving Machine Learning jobs near you
Infographic showing various Privacy Preserving Machine Learning job openings in Detroit, MI as of June 2026, with employment types broken down into 25% Full Time, 73% Part Time, 1% Temporary, and 1% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $114,346 per year, or $55 per hour.

Data Scientist

OneMagnify

Detroit, MI • On-site

$120 - $170/hr

Other

Re-posted 11 days ago

Job description

Data Scientist Role Summary

OneMagnify's Data Scientists sit at the intersection of client strategy and technical delivery, turning complex business questions into models, analyses, and insights that clients actually use to make decisions. You'll work alongside Data Engineering, AI, and cross‑functional teams to design and deploy solutions that span the full analytics lifecycle, from data integration and quality to predictive modeling and advanced analytics. This role is a fit for someone who wants to do serious technical work and see it matter in the real world.

The Impact You'll Have

The clients you support are making high‑stakes decisions about customers, markets, and products. Your models—forecasting demand, segmenting audiences, and optimizing spend—become the analytical backbone of how they operate. When your work is right, it drives measurable outcomes. When it’s wrong, someone notices. That accountability is part of what makes this role interesting. You will also contribute to building the analytics capabilities OneMagnify delivers at scale, writing code and documentation that others can reproduce, maintain, and extend. Shipping a model is the beginning, not the end.

What You'll Do
  • Build and validate analytical models.
  • Design, deploy, and monitor models including forecasting, classification, regression, and segmentation.
  • Conduct A/B testing and causal analyses with rigorous experimental design and clear documentation.
  • Develop optimization solutions (linear, mixed‑integer, multi‑objective) and ensure reproducibility across the full model lifecycle.
  • Own data integration and quality: integrate data from multiple sources, develop data‑quality reporting that surfaces issues before they become client problems, conduct root‑cause analysis on data anomalies, and validate database changes prior to release.
  • Use Databricks for large‑scale data processing and machine learning workflows.
  • Translate requirements into technical solutions by partnering with business and engineering teams to elicit requirements, define business rules, and turn them into technical specifications.
  • Document solutions clearly enough that someone else can maintain and extend your work, ensuring alignment between what clients ask for and what gets built.
  • Communicate findings to varied audiences: synthesize and present analytical findings to internal and external stakeholders, including executive‑level audiences, with the judgment to handle complex or sensitive inquiries with care.
  • Build metrics and KPI reports that inform real business decisions, not just dashboards that get ignored.
  • Prepare visualizations in Tableau and Power BI that make complex outputs accessible.
  • Support collaborative development using Git/GitLab for version control, reproducibility, and collaborative code development.
  • Collaborate with engineering teams to implement MLOps practices—including model deployment, monitoring, and end‑to‑end lifecycle management using tools such as MLflow.
  • Adhere to data governance, privacy, and compliance standards across all work.
What You’ll Need
  • BA/BS in Computer Science, Statistics, Mathematics, MIS, Marketing Research, or a related quantitative field—or equivalent practical experience.
  • 2–5+ years of hands‑on analytics, including predictive modeling, A/B testing, and optimization.
  • Advanced SQL and Python; strong ability to query, manipulate, and interpret data from databases and data warehouses.
  • Hands‑on experience with Databricks for large‑scale data processing and machine learning workflows.
  • Proficiency with Tableau and/or Power BI for visualization and reporting.
  • Experience with Git/GitLab for version control and collaborative development.
  • Strong Excel and PowerPoint skills.
  • Proven ability to present analyses to management and collaborate with both business and technical stakeholders.
  • Experience diagnosing and resolving data‑quality issues across multiple platforms.
  • Understanding of data governance, privacy, and compliance standards.
  • Familiarity with Master Data Management (MDM) concepts and how they apply to data quality and integration.
Future‑Ready Skills (Nice to Have)
  • Proficiency with SAS or R in an applied analytics environment.
  • Familiarity with automotive or VIN data and complex industry‑specific data structures.
  • Exposure to AI‑enabled analytics workflows or automation within a data science context.
  • Experience working in integrated marketing, consulting, or digital services environments where analytics supports client‑facing delivery.
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