Lead Data Scientist

System Soft Technologies; Town of Brookfield (WI); On-site; USD 180,000 - 240,000; Full time

Job summary

System Soft Technologies seeks a senior data science leader with 10+ years of professional AI/ML experience and strong hands-on expertise in traditional ML and Generative AI/NLP. You will drive commercial AI/ML solutions, lead cross-functional teams, and translate business needs into scalable data science outcomes.

Experience with EHR data or unstructured data is highly valued, along with strong Python, ML engineering, and cloud ecosystem knowledge.

Qualifications

• 10+ years in Data Science with measurable business impact.
• Expert-level Python; experience with R and SQL.
• Strong ML and NLP expertise, incl. GenAI.
• Experience with model validation, A/B testing.
• Hands-on with transformers and DL, transfer learning.
• Familiarity with Databricks or cloud ML ecosystems.
• ML Engineering/MLOps incl. CI/CD, GitHub Actions, Docker.
• Experience with EHR data or unstructured data.

Skills

AI/ML leadership

Deep learning

NLP & GenAI

Model validation

Transformers

Cross-functional collaboration

MLOps

EHR data experience

Education

PhD in Education

Data Science degree

CS/Statistics background

Tools

Python

R

SQL

Databricks

MLflow

Git

Docker

GitHub Actions

Linux

CI/CD

Job description

We’re looking for a senior data science leader with 10+ years of professional AI/ML experience and strong hands‑on expertise in both traditional ML and Generative AI/NLP.

Must have:

10yrs in Data Science, EHR & PhD (Education)

Key Requirements:

• 10+ years building commercial AI/ML solutions with measurable business impact
• Expert-level Python; experience with R and/or SQL
• Strong expertise in traditional ML, including regression, decision trees, Random Forest, XGBoost/LightGBM/CatBoost, ensemble methods, clustering, PCA, and anomaly detection
• Strong knowledge of model validation, cross-validation, hyperparameter optimization, and A/B testing
• Hands‑on experience with deep learning, neural networks, transformers, and transfer learning
• Expert knowledge of NLP, including text preprocessing, TF-IDF, embeddings, topic modeling, sentiment analysis, and NER
• Strong Generative AI/LLM expertise, including model evaluation, fine‑tuning, and integrating local/commercial LLMs
• Hands‑on experience building GenAI applications such as RAG systems, LLM evaluation frameworks, or internal GenAI tools
• Expertise with Databricks or a similar cloud‑based ML ecosystem, including MLflow, experimentation, data catalogs, and compute configuration
• Knowledge of ML Engineering/MLOps, including CI/CD, GitHub Actions, Docker, AWS Lambda, and Linux
• Strong software engineering practices including Git, unit testing, local development, and environment management
• Experience working with Electronic Health Records (EHR) and/or unstructured data is highly valuable
• Ability to partner with Product, Business Development, ML Engineering, and IT teams and translate business needs into scalable data science solutions
• Relevant degree in Computer Science, Data Science, Statistics, Mathematics, Actuarial Science, Economics, or a related field