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Senior Python Data Analyst Jobs in Ann Arbor, MI

Expeditors

Data Engineer III/Senior (Analytics)

Romulus, MI

$102K - $138K/yr

Building enterprise analytics solutions using Microsoft Fabric, Databricks, SQL, Python, and Power ... Senior Data Engineer: * Bachelor's degree with 10+ years, Master's with 5+ years, or PhD with 3+ ...

Expeditors

Data Engineer III/Senior (Analytics)

Romulus, MI · On-site

$102K - $138K/yr

Building enterprise analytics solutions using Microsoft Fabric, Databricks, SQL, Python, and Power ... Senior Data Engineer: * Bachelor's degree with 10+ years, Master's with 5+ years, or PhD with 3+ ...

Remora

Senior Performance Analyst

Wixom, MI

$84K - $111K/yr

Remora is seeking a Senior Performance Analyst to build the analytical foundation for our next ... Proficiency in Python, R, or another scripting language for data analysis and statistical modeling.

Remora

Senior Performance Analyst

Wixom, MI · On-site

$84K - $111K/yr

Remora is seeking a Senior Performance Analyst to build the analytical foundation for our next ... Proficiency in Python, R, or another scripting language for data analysis and statistical modeling.

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Senior Python Data Analyst information

See Ann Arbor, MI salary details

$53.8K

$97.1K

$132.6K

How much do senior python data analyst jobs pay per year?

As of Aug 18, 2026, the average yearly pay for senior python data analyst in Ann Arbor, MI is $97,081.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,100.00 and $106,100.00 per year, depending on experience, location, and employer.

What is the difference between Senior Python Data Analyst vs Data Scientist?

AspectSenior Python Data AnalystData Scientist
Required CredentialsBachelor's in Data Science, Statistics, or related field; Python proficiencyBachelor's or Master's in Data Science, Computer Science, or related; Python, R, machine learning skills
Work EnvironmentData analysis teams, business units, reportingResearch, model development, advanced analytics
Employer & Industry UsageBusiness, finance, marketing, healthcareTech companies, research institutions, finance, healthcare
Common Search & ComparisonYesYes

While both roles require Python skills and data analysis expertise, Data Scientists typically engage in advanced modeling, machine learning, and research tasks, whereas Senior Python Data Analysts focus more on interpreting data, generating reports, and supporting business decisions.

What are the most commonly searched types of Python Data Analyst jobs in Ann Arbor, MI?

The most popular types of Python Data Analyst jobs in Ann Arbor, MI are:

What are popular job titles related to Senior Python Data Analyst jobs in Ann Arbor, MI?

For Senior Python Data Analyst jobs in Ann Arbor, MI, the most frequently searched job titles are:

What job categories do people searching Senior Python Data Analyst jobs in Ann Arbor, MI look for?

The top searched job categories for Senior Python Data Analyst jobs in Ann Arbor, MI are:

What cities near Ann Arbor, MI are hiring for Senior Python Data Analyst jobs?

Cities near Ann Arbor, MI with the most Senior Python Data Analyst job openings:

Senior Python Data Analyst jobs near you
Infographic showing various Senior Python Data Analyst job openings in Ann Arbor, MI as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $97,081 per year, or $46.7 per hour.

Senior Data Scientist (Consultant)

Strategic Staffing Solutions

Detroit, MI • Hybrid

Full-time

Posted 10 days ago

Job description

Job Description STRATEGIC STAFFING SOLUTIONS (S3) HAS AN OPENING. Senior Data Scientist (Consultant) Detroit, MI (Hybrid/Onsite Tues-Thurs) W2 contract role 12 months with opportunity to extend Competitive salary with benefits Role Summary We are looking for a senior practitioner who has successfully built and deployed at least one production-grade Retrieval Augmented Generation (RAG) solution. The ideal candidate should be capable of working across the full AI lifecycle, including ingestion, retrieval, modeling, APIs, testing, deployment, monitoring, and operational support.

The candidate should also have strong expertise in classical machine learning and statistics and be experienced in delivering explainable, auditable AI solutions within regulated, human-in-the-loop environments. Additional details: Machine Learning & Applied AI Strong background in supervised and unsupervised learning, including: Classification Ranking Clustering Anomaly detection Predictive modeling Experience selecting evaluation metrics and designing representative test datasets Hands-on experience with explainability techniques such as SHAP, LIME, and feature importance analysis Experience designing human-in-the-loop AI systems with review, escalation, override, and feedback mechanisms Generative AI & Retrieval Production experience with: RAG architectures Embeddings Semantic search Re-ranking Prompt engineering Vector databases Experience building enterprise copilots, assistants, or document-grounded decision-support systems Ability to evaluate retrieval quality, grounding, hallucination risk, answer quality, and failure modes Experience with open-source or locally hosted LLMs preferred Python & Software Engineering Advanced Python skills, including: Pandas NumPy Scikit-learn PyTorch (or similar deep learning framework) Ability to develop maintainable, production-quality code rather than notebook-only solutions Experience with: Git and code reviews Unit and integration testing CI/CD pipelines API development Docker or Podman Experience with agentic development is a plus Comfortable working in both local and cloud environments Data Engineering & Integration Strong SQL and ETL/ELT development skills Experience integrating: REST APIs Enterprise document repositories Workflow systems Batch and incremental data pipelines Experience with PostgreSQL, SQL Server, data lake architectures, data lineage, and data quality controls Ability to design resilient ingestion pipelines for documents, metadata, attachments, and changing source-system records *Beware of scams. S3 never asks for money during its onboarding process.

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