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Matt Wallaert
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HR Data Scientist

Capgemini

Capgemini

People & HR, Data Science
Romania
Posted on Oct 8, 2024

Qualifications

- Strong level of knowledge acquired over time in a professional HR analytics/data science position, a minimum of 5 years of experience.
- Experience with the field of People Analytics specifically, of an analytical / business partnering role in a People / HR function or with a human / psychology / workplace element;
- Extensive experience applying statistical, data science and advanced analytics techniques to answer business questions, incl. using storytelling and having the ability to explain complex and contentious subject matter;
- Strong knowledge, ability to apply and explain statistical concepts and techniques, both descriptive and inferential, incl. modelling, time-series analysis, with the ability to select the most appropriate techniques for a given use case;
- Ability to recognize and interpret business requirement and translate this need into technical design of an analytics solution;
- Architectural and/or feature knowledge of one or more of the listed Languages or Packages: Python, R, MATLAB, STATA, SPSS, SAS, PowerBI, Tableau;
- Experience applying advanced statistical methods and techniques;
- Evidence of post qualifying and continuing professional development;
- Detail-oriented expert with a strong analytical skill;
- Desirable: French/German language speak to a high level of fluency.

Job Responsibilities

- Provide leadership and advisory support to clients looking to develop their practice around People Data and Analytics and deepen the way in which data enhances their People/HR function;
- Work with clients on their HR Analytics and Research needs, design and deliver data science projects;
- Develop analytical tools and products that use a range of structured and unstructured data sets from both people and non-people systems to make predictions in critical areas for clients’ People Experience;
- Develop long-term mutually beneficial relationships with clients that allow anticipation of client requirements and an advisory style relationship;
- Develop data visualisations that support clients to tell stories with data, garnering support for projects and initiatives that are indicated by the data for prioritisation;
- Coach, mentor and develop junior resources;
- Deliver work in a structured manner, finding a balance between creativity and practicality to ensure we meet client standards efficiently within the agreed timescales;
- Drive innovation and continually develop the team’s knowledge and own knowledge in the areas of statistics, People Analytics, Machine Learning, AI and related topics.