Applied Data Scientist

1 Month ago • 5 Years + • Data Analysis

Job Summary

Job Description

Mercer is seeking an Applied Data Scientist to support internal teams in transforming data into actionable insights and LLM-powered features. This role involves validating business assumptions, performing deep data analysis, contributing to LLM feature development using frameworks like OpenAI or Hugging Face, and advising on data structuring. The Data Scientist will also be responsible for creating documentation and collaborating with stakeholders to align data strategies with business goals. The ideal candidate will have 5+ years of experience in data science or machine learning, proficiency in SQL and Python, and experience with data visualization tools like Tableau or Power BI.
Must have:
  • 5+ years of experience in Data Science, ML, or advanced Data Analytics
  • Proficiency in SQL for querying large datasets
  • Strong Python programming skills
  • Familiarity with LLM frameworks (OpenAI, Hugging Face)
  • Experience with data visualization tools (Tableau, Power BI)
  • Solid understanding of data modeling and statistical testing
  • Excellent communication skills
Good to have:
  • Experience in HR, people management, or compensation domains
  • Experience in distributed, cross-functional product teams
  • Knowledge of MLOps best practices

Job Details

GT was founded in 2019 by a former Apple, Nest, and Google executive. GT’s mission is to connect the world’s best talent with product careers offered by high-growth companies in the UK, USA, Canada, Germany, and the Netherlands.

On behalf of Mercer, GT is looking for an Applied Data Scientist to support internal teams across Mercer, helping turn data into actionable insights and LLM-powered features.

**Contract Duration: 6+ months (with possible extension based on performance)

About the Client

Mercer is a global consulting leader in advancing health, wealth, and career outcomes for organizations and individuals. Headquartered in New York City, Mercer operates in over 130 countries with more than 25,000 employees and 180+ office locations worldwide. As part of Marsh McLennan, Mercer provides data-driven insights and tailored solutions in areas such as HR transformation, compensation and benefits, workforce analytics, and employee experience. The company fosters a collaborative, inclusive, and purpose-driven culture that values innovation, integrity, and impact.

About the Role:

We are looking for experienced and curious Data Scientists to join a dynamic data enablement team that operates across multiple product groups. This role focuses on empowering internal teams with actionable insights, LLM-enhanced feature development, and data structure expertise. You will play a key role in building scalable analytical processes and supporting strategic decision-making.

Responsibilities:

  • Validate Business Assumptions: Analyze and test key project assumptions to support reliable decision-making

  • Perform Deep Data Analysis: Extract meaningful insights from complex datasets across products and teams

  • LLM Feature Development: Contribute to the design and implementation of product features using Large Language Models (e.g., OpenAI, Hugging Face)

  • Data Structuring & Guidance: Advise teams on data structuring for optimal analytical use

  • Documentation: Create clear, practical guidelines and documentation for data usage, pipelines, and insights

  • Stakeholder Collaboration: Engage with product managers and cross-functional stakeholders to align data strategies with business goals

Essential knowledge, skills & experience:

  • 5+ years of experience in a Data Science, Machine Learning, or advanced Data Analytics role

  • Proficiency in SQL for querying large datasets

  • Strong programming skills in Python (R is a plus) for statistical analysis and modeling

  • Familiarity with LLM frameworks such as OpenAI or Hugging Face

  • Experience with data visualization tools such as Tableau or Power BI

  • Solid understanding of data modeling, exploratory data analysis, and statistical testing

  • Excellent communication skills for technical and non-technical stakeholders

Nice-to-have:

  • Experience in the HR, people management, or compensation domains

  • Experience working in distributed, cross-functional product teams

  • Knowledge of MLOps best practices or experience deploying data science models to production

Interview Process

  1. Interview with GT Recruiter

  2. Technical Interview

  3. Competency interview

  4. Final Interview

  5. Reference Check

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