Data Scientist

About the Role

Key Responsibilities

• Execute analytical experiments methodically to help solve various problems and make a true impact across various domains and industries.
• Research and apply state-of-the-art artificial intelligence methods and innovative statistical models.
• Identify relevant data sources and sets to mine for client business needs, and collect large structured and unstructured datasets and variables.
• Process, cleanse, and verify the integrity of data used for analysis.
• Develop code for predictive/prescriptive models with applied machine learning and other modeling techniques.
• Clearly document and present methodology, assumptions, and findings to stakeholders.
• Work with a wide range of stakeholders and functional teams to improve business outcomes.
• Deliver in a fast-paced, team-oriented work environment.
• Adapt quickly to changing needs across data wrangling, exploration, analysis, and visualization.
• Articulate trade-offs between analytic techniques, recommend courses of action, and update leadership on project outcomes.
• Perform analysis to discover insights in large data sets using advanced analysis methods, data tools, and models.
• Create and test algorithms and simulations to evaluate different courses of action.

Requirements

• Bachelor's degree in Data Science or related field.
• 2+ years experience in Data Science or Data analysis.
• Proficiency in programming languages like Python or R.
• Experience with AI frameworks like TensorFlow or PyTorch.
• Familiarity with Retrieval Augmented Generation (RAG) architectures and Large Language Models (LLM).
• Developing data pipelines to support analytics.
• Applying advanced analytics and machine learning techniques.
• Documenting and communicating analysis results.
• Familiarity with SQL and BI tools (Tableau, Qlik, etc.).
• Strong analytical and problem-solving skills.
• Hands-on experience with driving analytic insights and workflow automation.
• Ability and motivation to self-teach and stay current with analytics best practices.
• Data wrangling skills.

Nice to Have

• Solid understanding of applied machine learning methods and algorithms.
• Exploratory Data Analysis and Workflow Improvement.
• Applied statistics skills, such as distributions, statistical testing, regression, etc.
• Proficiency in data query languages like SQL and understanding various data structures.
• Ability to use data visualization to communicate insights.
• Experience designing and developing AI agents and implementing agentic workflows.
• Knowledge of agentic AI frameworks such as LangGraph and standards like Model Context Protocol (MCP).
• Experience with text mining and Natural Language Processing techniques such as Named Entity Recognition and Text Classification.
• Familiarity with graph analysis tools like Neo4J and Cypher.
• Experience with cloud platforms like Databricks, Azure AI Foundry, Amazon Bedrock, Amazon SageMaker.
• Experience with process automation, image analysis, and predictive/prescriptive analysis.

Qualifications

• Educational background: Bachelor's degree in Data Science or related field.
• Experience: 2+ years in Data Science or Data analysis.

Benefits & Perks

• Competitive lifestyle benefits including 401K plan with company match.
• Medical, dental, vision, life insurance, AD&D, flexible spending account, disability, paid time off, or flexible work schedule.
• Support for career advancement through professional training and development.