Senior Data Scientist (Consultant)

Strategic Staffing Solutions; Detroit (MI); Hybrid; USD 90,000 - 130,000; Full time

Job summary

Strategic Staffing Solutions in Detroit, MI seeks a Senior Data Scientist (Consultant) for a 12-month W2 contract in a hybrid/on-site role. The candidate will lead development of production-grade RAG solutions and end-to-end AI lifecycle management, with emphasis on explainable, auditable AI in regulated environments.

Key work includes building embeddings, retrieval systems, and enterprise copilots. Strong Python, ML, and software engineering skills are required, along with experience in

Qualifications

• Production-grade ML projects with RAG
• Explainable, auditable AI in regulated environments
• Experience with AI lifecycle: ingestion, retrieval, modeling, APIs, testing
• Strong ML/statistics background

Responsibilities

• Design and deploy RAG-based retrieval systems
• Build enterprise copilots or document-grounded systems
• Evaluate retrieval quality and grounding
• Develop maintainable production-grade code

Skills

RAG architectures

Embeddings

Semantic search

Re-ranking

Prompt engineering

Vector databases

Explainability

Human-in-the-loop

Production ML

Evaluation metrics

Tools

Python

Pandas

NumPy

Scikit-learn

PyTorch

Git

CI/CD

API development

Docker

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