Lead Data Scientist - AI & Machine Learning - No C2C (Oshkosh, WI)
Lead data scientist (individual contributor) who owns AI/ML projects end to end for an enterprise: building and deploying predictive models, MLOps pipelines, and generative AI/LLM solutions (RAG, agents, fine-tuning) with Python and SQL, while partnering with business stakeholders. Hybrid role in Oshkosh, WI; open only to US citizens eligible for secret clearance.
- Compensation
- $140K–$160K / yr
- Location
- Not listed
- Work setup
- Hybrid
- Seniority
- Lead
- Employment
- Full time
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- US Citizenship with eligibility for secret security clearance (no green card, TN, H1B, or F1 candidates)
- Bachelor's degree in Data Science, CS, Statistics, Math, Engineering, Operations Research, or related quantitative field, or equivalent experience
- 5+ years professional experience in data science, machine learning, advanced analytics, or related fields
- Experience independently developing and deploying AI/ML solutions into production
- Hands-on Python with Pandas, NumPy, Scikit-Learn, PyTorch, or TensorFlow
- Advanced SQL skills and experience with complex datasets
- Experience developing predictive models, ML pipelines, and AI-driven applications
- Working knowledge of Generative AI, LLMs, and modern AI application architectures
Nice to have
- Master's degree or PhD in a related quantitative field
- Experience building LLM applications, RAG architectures, intelligent agents, or fine-tuned models
- Experience with Databricks, Snowflake, or Apache Spark
- Familiarity with MLOps tools such as MLflow, Docker, Kubernetes, Kubeflow, or Airflow
- Experience with BI/visualization tools such as Power BI or Streamlit
- Experience with automated model monitoring, feature stores, or continuous model improvement
- Background in business analysis, business operations, or consulting
- Experience delivering AI/analytics solutions in a complex enterprise environment
- Ability to tie technical solutions to measurable financial or operational outcomes
Full description
This role is open ONLY to US Citizens as all candidates must be eligible for secret security clearance (clearance requires US Citizenship). Please note, clearance isn’t required to start (only eligibility). Candidates who are Permanent Residents (Green Card Holders), TN visa holders, H1B or F1 (OPT/CPT) candidates are NOT permitted in this role. This role is NOT open to corp2corp (C2C) or corp2hire (C2H).
Lead Data Scientist – AI & Machine Learning
Work Arrangement: Hybrid – 3 days onsite, 2 days remote
Compensation: $140,000–$160,000 annually + 10% bonus opportunity
Anticipated Start Date: January 4, 2027
Travel: Less than 10%
Relocation Assistance: Available for qualified candidates
Position Summary
We are seeking a highly skilled Lead Data Scientist to drive the development, implementation, and deployment of advanced analytics, machine learning, and artificial intelligence solutions across the enterprise.
This position operates at the intersection of business strategy and technical execution, partnering directly with business stakeholders to identify opportunities, translate operational challenges into data-driven solutions, and deliver measurable business value.
The ideal candidate combines strong technical expertise in AI, machine learning, and data science with business acumen, stakeholder engagement, and hands-on solution delivery. This is an individual contributor role requiring ownership of projects from initial business requirements and solution architecture through development, production deployment, and ongoing optimization.
Key Responsibilities
AI/ML Development & Technical Delivery
- Design, develop, test, and deploy production-ready machine learning models, predictive analytics solutions, and artificial intelligence applications.
- Own the end-to-end solution lifecycle, including business requirements gathering, data exploration, model development, validation, deployment, and performance monitoring.
- Develop and implement Generative AI and Large Language Model (LLM) solutions, including retrieval-augmented generation (RAG), intelligent agents, and model fine-tuning.
- Build supervised and unsupervised learning pipelines, statistical models, and advanced analytics frameworks to address complex business challenges.
- Collaborate with Data Engineering and DevOps teams to implement scalable MLOps practices, including CI/CD pipelines, model monitoring, data drift detection, and automated retraining.