Title:  Associate Data Scientist, D&T

Job Summary

The Associate Data Scientist, Digital & Transformation will support a multidisciplinary team in designing and developing innovative data-driven analytical products and solutions. This role involves applying advanced analytics, data mining, machine learning, and emerging Generative AI techniques to address business challenges and drive measurable outcomes.

Essential Duties and Responsibilities

• Apply statistical, machine learning, and Generative AI techniques to address strategic business problems.

• Retrieve, clean, and prepare structured, semi-structured, and unstructured data from diverse sources.

• Support exploratory analysis, algorithm design, model development, and advanced analytics under guidance.

• Contribute to building scalable, automated processes for data analysis, model validation, and deployment.

• Assist in developing tools to monitor and evaluate model performance, accuracy, and fairness.

• Create data-driven insights, dashboards, and visualizations for stakeholder communication.

• Collaborate with internal experts and cross-functional teams to operationalize AI solutions.

• Participate in research and prototyping with agentic AI frameworks (e.g., LangGraph, OpenAI Agents).

• Perform other related duties as assigned.

Additional Responsibilities

Education

• Bachelor’s degree in Computer Science, Mathematics, Statistics, Data Science, or another quantitative discipline with a strong academic record. 

Work Experience

• No min required 1+ years of related work experience required

Preferred Knowledge, Skills and Abilities

• Proficiency in Python for data manipulation, scripting, prototyping, and familiarity with AI-assisted coding.

• Foundational to advanced experience with machine learning technologies and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).

• Exposure to agentic AI frameworks (e.g., LangGraph, OpenAI Agents) and familiarity with agent patterns and their effective applications.

• Solid understanding of AI system development, validation, and evaluation practices.

• Experience with Jupyter notebooks, Anaconda environments, or similar tools for experimentation and workflow management.

• Strong grasp of statistics and data science methods (e.g., regression, hypothesis testing, probability distributions).

• Basic to intermediate knowledge of distributed systems, scalable computing approaches, and containerization (e.g., Docker).

• Exposure to cloud platforms (Azure, AWS) and related AI services such as Azure ML, Azure AI Foundry/OpenAI platform, Azure Cognitive Services, and AI Search.

• Familiarity with web services, microservices, and REST APIs, as well as building and working with data architectures.

• Basic knowledge of BI/visualization tools (e.g., Power BI, Microsoft Fabric).

• Understanding of modern computer vision techniques.

• Product development mindset with the ability to work in fast-paced, agile environments.

• Independent and creative approach to problem-solving with the ability to prioritize effectively and deliver with urgency.

• Strong communication and collaboration skills in global and virtual team settings.

License and Certifications

Travel Requirements

Physical Requirements

Additional Requirements