Senior Data Scientist IRC257661

GlobalLogic is seeking an experienced Big Data Scientist to help us improve and help to develop the new modern personalized digital platform. Every engineer in our team has an opportunity to make a tremendous impact. We are looking for innovative and passionate engineer who want to take ownership of features and projects and collaborate with other engineers and product managers to evaluate, design, and implement from top to bottom. We will provide opportunities to work with cutting-edge technology that helps millions of people save their/money.

We seek creative and motivated engineers to work on our digital coupon solution. There are a wide variety of challenges that have been and still need to be solved. You will have opportunities for growth and development. You will be part of a team that works on services that have served over 1 billion coupons.

Project for customer base in the U.S. shaping the ways CPG brands operate in the market. Work with us using the latest technology and influence the way over 50 million shoppers act each day.


Requirements
5 to 8 years of hands-on experience in machine learning, data science, and optimization, with a track record of building and deploying AI-driven solutions in a production environment.
Expert proficiency in Python and Databricks, with demonstrated experience in Azure DevOps, Spark, and cloud-based ML operations for scalable data processing and model deployment.
Strong foundation in exploratory data analysis (EDA), statistical modelling, and feature engineering, with the ability to uncover patterns, detect anomalies, and optimize model inputs.
Hands-on experience developing predictive, optimization, and generative AI models, ensuring business relevance through measurable outcomes and iterative improvements.
Proven ability to implement and manage CI/CD pipelines for machine learning models, automating deployment, monitoring, and retraining to enhance efficiency and reliability.
Experience leveraging GenAI tools (e.g., ChatGPT, Databricks Assistant, or equivalent) to accelerate solution development, debug complex issues, and optimize coding workflows.
Commitment to continuous learning and staying ahead of industry advancements, actively researching and integrating emerging machine learning, AI, and data science trends.

Job responsibilities
As a Senior Data Scientist, you will design, develop, and deploy advanced machine learning and optimization solutions that drive business impact. This role requires a mix of technical expertise, problem-solving, and business acumen to build scalable pipelines, optimize models, and leverage GenAI tools for efficiency. You’ll work across the full data science lifecycle, collaborating with cross-functional teams to translate complex challenges into actionable insights. Success in this role means delivering high-quality solutions with minimal supervision while continuously innovating and staying ahead of industry advancements.

Build and optimize end-to-end machine learning and optimization pipelines in Databricks using Python and Azure DevOps, ensuring efficiency, scalability, and alignment with business objectives.
Perform in-depth exploratory data analysis (EDA) to detect anomalies, uncover patterns, and generate actionable insights, using statistical methods to inform data science solutions.
Design and implement feature engineering strategies to enhance model accuracy and reliability, leveraging domain expertise and automation tools.
Develop, train, and optimize predictive, optimization, and generative AI models, ensuring measurable business impact through continuous improvement.
Implement CI/CD workflows for machine learning models, automating deployment, monitoring, and retraining processes for efficiency and consistency.
Leverage GenAI tools (e.g., ChatGPT, Databricks Assistant) to accelerate solution development, enhance debugging, and optimize coding efficiency.
Write modular, maintainable, and well-documented code, following best practices for scalability, version control, and secure coding standards.
Absorb and apply business concepts and stakeholder language, ensuring data science solutions align with organizational goals and decision-making.
Stay ahead of industry advancements, continuously researching new methodologies, tools, and frameworks to integrate state-of-the-art techniques.
Collaborate effectively with cross-functional teams, including engineers, project managers, and business stakeholders, to drive successful implementations.
Demonstrate problem-solving resilience, proactively addressing technical blockers and seeking the right resources or alternative solutions to maintain project momentum.
Track and analyze model performance using key metrics, refining solutions to enhance real-world business impact and decision support.