Associate Data Scientist

Overview

We are seeking a passionate and innovative GenAI Engineer/Data Scientist to join our team. This role involves developing GEN AI solutions and predictive AI models, deploying them in production environments, and driving the integration of AI technologies across our business operations. As a key member of our AI team, you will collaborate with diverse teams to design solutions that deliver tangible business value through AI-driven insights.

• Application Architecture Design, Development, & Integration:
  Familiarity with API architecture and components such as external interfacing, traffic control, runtime execution of business logic, data access, authentication, and deployment.
• AI & Machine Learning Models Development:
  Develop generative and predictive AI models (including NLP, computer vision, etc.). Familiarity with cloud platforms (e.g., Azure, AWS, GCP) and big data tools (e.g., Databricks, PySpark) to develop AI solutions. Familiarity with intelligent autonomous agents for complex tasks and multimodal interactions. Familiarity with agentic workflows that utilize AI agents to automate tasks and improve operational efficiency.
• Model Deployment & Maintenance:
  Deploy AI models into production environments, ensuring scalability, performance, and optimization. Monitor and troubleshoot deployed models and pipelines for optimal performance.
• Design and maintain data pipelines for efficient data collection, processing, and storage (e.g., data lakes, data warehouses).
• Emerging Technologies: stay at the forefront of emerging AI techniques, tools, and trends; participate in internal and external training and relevant discussions.
• Collaboration & Communication:
  Collaborate with cross-functional teams to align AI projects with business requirements and strategic goals.
• Contribute to developing and harvesting reusable assets and demos, and support sales pitches.
• Communicate complex AI concepts and results to non-technical stakeholders.

• Education:
  
  Bachelor’s or greater degree in Machine Learning, AI, or equivalent professional experience.
• Experience:
  
  Minimum of 1 year of professional experience in AI, application development, machine learning, or a similar role. Experience in model deployment, MLOps, model monitoring, and managing data/model drift. Experience with predictive AI (e.g., regression, classification, clustering) and generative AI models (e.g., GPT, Claude LLM, Stable Diffusion).
• Technical
  
  Skills:
  
  Proficiency in programming languages such as Python and SQL. Proficiency in URLs and API Endpoints, HTTP Requests, Authentication Methods, Response Types, JSON/REST, Parameters and Data Filtering, Error Handling, Debugging, Rate Limits, Tokens, Integration, and Documentation. Proficiency with cloud platforms (e.g., AWS, Azure) and big data tools (e.g., Databricks, PySpark). Familiarity with AI frameworks such as Lang Chain and machine learning libraries like Tensor Flow, PyTorch, and scikit-learn.
  
  Knowledge of deployment tools (e.g., Azure Dev Ops, Docker, AWS ECS/EKS/Fargate) and CI/CD pipelines (AWS Cloud Formation, Code Deploy). Understanding of data engineering principles, including experience with SQL and No
  
  SQL databases (e.g., MySQL, Mongo
  
  DB, Redis).
• Additional
  
  Skills:
  
  Strong problem-solving and troubleshooting skills. Familiarity with generative AI techniques, such as retrieval-augmented generation (RAG). Experience with graph database technology (e.g., Neo4J) is a plus. Ability to collaborate effectively across teams. Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

The base compensation range for this role in the posted location is $46,400 to $111,090. Capgemini provides compensation range information in accordance with applicable laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction, including: geographic location, education and qualifications, certifications, relevant experience and skills, seniority and performance, market and business considerations, and internal pay equity. It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be…