Thomson Reuters

Senior Data Scientist

Thomson Reuters

full-time

Posted on:

Origin:  • 🇮🇳 India

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Job Level

Senior

Tech Stack

AWSPythonSQLTableau

About the role

  • Engage with stakeholders, business analysts, and project teams to understand data requirements.
  • Work across multiple business domains, including Customer Service, Finance, Sales, and Marketing.
  • Design, develop, and deploy predictive models and machine learning algorithms to address business challenges.
  • Explore, visualize, and prepare diverse datasets for analysis and problem-solving.
  • Build machine learning and statistical models, including generative AI solutions.
  • Apply Natural Language Processing (NLP) techniques to extract insights from text data.
  • Design database models and aggregate data as needed for modeling.
  • Create visualizations and build dashboards in Tableau and/or PowerBI.
  • Extract and present business insights using data storytelling techniques.
  • Analyze large and complex datasets to identify trends and generate meaningful insights.
  • Collaborate with product managers, engineers, and stakeholders to define requirements and deliver solutions.
  • Mentor and guide junior data scientists and analysts.
  • Clearly communicate findings and recommendations to both technical and non-technical audiences.
  • Stay current with the latest data science methodologies, tools, and best practices.
  • Promote the adoption of data science techniques and foster a data-driven culture within the organization.

Requirements

  • 6-10 Years of experience in Machine Learning, AI, and Data Science.
  • A degree in a quantitative field (e.g., Computer Science, Statistics) is preferred.
  • Proven technical expertise and business acumen.
  • Proficiency in machine learning, statistical modeling, and generative AI techniques.
  • Advanced skills in Python, SQL & Snowflake
  • Experience with Tableau and/or PowerBI.
  • Hands-on experience with Amazon Web Services (AWS) and SageMaker.
  • Ability to build data pipelines using tools such as Alteryx and AWS Glue.
  • Experience in predictive analytics for customer retention, upsell/cross-sell, customer segmentation, recommendation engines, and building generative AI solutions (e.g., GPT, Llama).
  • Practical knowledge of prompt engineering and working with Large Language Models, Retrieval Augmented Generation (RAG), and AI agents.
  • Experience in business domains such as Customer Service, Finance, Sales, and Marketing.
  • Familiarity with NLP techniques, including feature extraction, word embeddings, topic modeling, sentiment analysis, classification, sequence models, and transfer learning.
  • Knowledge of AWS APIs for machine learning.
  • Strong presentation and data storytelling skills, with the ability to communicate complex results clearly at all organizational levels.