Data Scientist

Role snapshot

• Title: Data Scientist
• Location: Indianapolis, IN (hybrid, 2–3 days on-site)
• Engagement: Full-time, placed with an Augmented enterprise client
• Level: Intermediate to Senior (4+ years in data science or applied ML)
• Reports to: Data Science / Analytics Lead

About the role

• Augmented is hiring a Data Scientist to build and deploy machine learning and GenAI solutions for one of our large enterprise clients in a regulated industry. You will turn business questions into models that ship, from exploration through production and monitoring.
• You will join a small, senior delivery team that works directly with client business and technology stakeholders. The work spans predictive modelling, experimentation and LLM-based applications, with a strong focus on measurable business impact.

Key responsibilities

• Partner with business stakeholders to frame problems, define success metrics and prioritise use cases
• Explore and prepare large, complex data sets; engineer features with data engineering partners
• Build, validate and tune models for prediction, classification, forecasting, segmentation and optimisation
• Design and analyse 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 with MLOps practices: versioning, CI/CD, monitoring and retraining
• Ensure models are explainable, fair, well documented and compliant with regulatory requirements
• Communicate findings clearly through visualisations, presentations and written recommendations
• Mentor junior team members and contribute to reusable tools and best practices

Required qualifications

• 4+ years 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
• 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
• Experience with MLOps tooling such as MLflow, Git and CI/CD
• 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 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 or distributed computing for large-scale data
• Consulting or client-facing delivery background

Tech stack

• Languages: Python, SQL, R (a plus)
• ML libraries: scikit-learn, XGBoost / LightGBM, PyTorch, TensorFlow
• GenAI: LLM APIs, LangChain / LlamaIndex, vector databases
• Platforms: Databricks, Snowflake, AWS SageMaker or Azure ML
• MLOps: MLflow, Git, CI/CD pipelines, Docker
• Data: Spark, dbt, cloud data lakes
• Visualization: Power BI, Tableau, Plotly / Streamlit

Why Augmented

• Augmented is an AI-native engineering delivery hub serving large enterprises in Life Sciences and Fintech, with teams in Toronto and the US.
• Build ML and GenAI solutions that reach production at enterprise scale
• Small, senior teams with direct access to client decision-makers
• Exposure to AI-native delivery practices and modern tooling
• Compensation: [salary range to confirm] plus benefits

• How to apply
• Apply through this posting with your resume and a short note on a model you took to production (problem, approach, measured impact).
• Augmented is an equal opportunity employer. Accommodations are available on request at any stage of the hiring process.