Data Scientist
The Data Scientist at Confidential Client will develop and deploy machine learning and GenAI solutions for a large regulated enterprise client, focusing on measurable business impact. This role involves partnering with stakeholders to frame problems, building and validating predictive models, designing experiments, and ensuring models meet regulatory and explainability standards. The position offers a hybrid work environment and requires strong expertise in Python, cloud ML platforms, and MLOps practices.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT Services and IT Consulting.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Role Overview
Confidential Client is seeking a mid-to-senior Data Scientist to design, build, and deploy machine learning and GenAI solutions for an enterprise-scale, regulated client. You will work on a small, senior delivery team partnering directly with client business and technology stakeholders to convert high-impact business questions into production models and monitored applications.
What You’ll Do
- Partner with business stakeholders to frame problems, define success metrics, and prioritize use cases
- Explore and prepare large, complex datasets and collaborate with data engineering partners on feature engineering
- Build, validate, and tune models for prediction, classification, forecasting, segmentation, and optimization
- Design and analyze experiments (A/B tests, causal inference) to measure impact
- Develop GenAI and LLM-based solutions including retrieval-augmented generation (RAG), evaluation, and guardrails
- Deploy models to production using MLOps best practices: versioning, CI/CD, monitoring, and retraining
- Ensure models are explainable, fair, documented, and compliant with regulatory requirements
- Communicate findings clearly via visualizations, presentations, and written recommendations
- Mentor junior team members and contribute to reusable tools, libraries, and delivery practices
Qualifications (Required)
- 4+ years of experience in data science or applied machine learning with models delivered to production
- MS or PhD in Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field — or equivalent experience
- Strong Python (pandas, scikit-learn, and PyTorch or TensorFlow) and advanced SQL skills
- Solid foundation in statistics, experimental design, and ML evaluation
- Hands-on experience with at least one cloud ML platform (Databricks, AWS SageMaker, Azure ML, or Vertex AI)
- Familiarity with MLOps tooling such as MLflow, Git, and CI/CD pipelines
- Ability to explain complex results to non-technical audiences
- Authorized to work in the United States
Nice to Have
- Production GenAI experience: LLM APIs, vector databases, prompt engineering, and LLM evaluation frameworks
- Time-series forecasting, NLP, or computer vision experience
- Experience in Life Sciences (clinical, commercial, or real-world data) or Financial Services (risk, fraud, credit)
- Familiarity with model risk management, GxP, or other regulatory frameworks
- Spark / distributed computing experience for large-scale data
- Consulting or client-facing delivery background
Tech Stack & Tools
- Languages: Python, SQL (R is a plus)
- ML libraries: scikit-learn, XGBoost / LightGBM, PyTorch, TensorFlow
- GenAI: LLM APIs, LangChain / LlamaIndex, vector DBs
- Platforms: Databricks, Snowflake, AWS SageMaker, Azure ML
- MLOps: MLflow, Git, CI/CD pipelines, Docker
- Data: Spark, dbt, cloud data lakes
- Visualization: Power BI, Tableau, Plotly, Streamlit
Work Location & Schedule
- Location: Indianapolis, IN (hybrid — typically 2–3 days on-site)
- Employment Type: Full-time
Why Join
- Deliver ML and GenAI solutions at enterprise scale for high-impact clients
- Join a small, senior team with direct stakeholder access and influence
- Gain exposure to modern AI-native delivery practices and tooling
- Work in a collaborative, client-facing environment that values measurable business outcomes
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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