Company:

Mercer

Description:

Senior Analyst - Data Science

 

What can you expect?

- Join the AI Engineering team in the international environment of Mercer Career Delivery.

- Enjoy numerous development and on-the-job learning opportunities.

- Benefit from flexible working hours and a remote or hybrid work model.

- Embrace a business casual dress code, along with integration and wellbeing events.

- Access an attractive benefits package, including private healthcare, a flexible benefits package (prepaid restaurant or shopping card topped up monthly, prepaid sports & culture card or Multisport card), language course co-financing, unlimited access to an online learning platform, and a retirement plan.

- Be part of a multilingual community that fosters an inclusive atmosphere.

- Work in a comfortable office located in the Warsaw city center (Al. Jerozolimskie 98, Pl. Zawiszy area).

- Gain valuable experience in an international organization with exposure to teams across the globe.

 

We will count on you to:

- Design, develop, and test prototypes of advanced AI/ML solutions for various business applications in close collaboration with Business and Operations teams.

- Collaborate with DevOps and other Technology teams to implement and deploy solutions that meet client and business needs while optimizing system performance.

- Monitor performance and recommend improvements.

- Identify opportunities to leverage AI for business transformation.

 

What you need to have:

- 1-2 years of professional experience in data science, machine learning, or artificial intelligence.

- Proficiency in English.

- A passion for technology and a willingness to evolve your skillset alongside technological advancements.

- Strong practical knowledge of Python, including coding best practices, version control, unit testing, and CI/CD.

- A good understanding of the LLM tech stack, including OpenAI API, vector stores, and MCP servers.

- Experience in building LLM-based solutions such as RAG, AI workflows, and AI agents, with evaluation and monitoring.

- Familiarity with machine learning processes, including planning, executing, and evaluating model training using scikit-learn and TensorFlow.

- Hands-on experience with AI-assisted programming.

- Understanding of fundamental tools and concepts: Linux, SQL, API, cloud computing, exploratory data analysis, and basic statistical concepts.

 

What makes you stand out:

- Experience with LLM frameworks (e.g., LangChain, Ragas, OpenAI Agents SDK).

- Familiarity with data/AI platforms (e.g., Databricks).

- Knowledge of deployment infrastructure (e.g., Docker, Kubernetes, AWS).

 

If you would like to apply for this position, please submit your application in English

Mercer, a business of Marsh McLennan (NYSE: MMC), is a global leader in helping clients realize their investment objectives, shape the future of work and enhance health and retirement outcomes for their people. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businesses: Marsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit mercer.com, or follow on LinkedIn and X.

Marsh McLennan is committed to creating a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, disability, ethnic origin, family duties, gender orientation or expression, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law.

Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one “anchor day” per week on which their full team will be together in person.