Data Scientist - People Analytics

This job is with ABB, an inclusive employer and a member of myGwork - the largest global platform for the LGBTQ+ business community.Please do not contact the recruiter directly.ABB is a worldwide provider of electrification and automation solutions, enabling a more sustainable and resource-efficient future.By combining its engineering know-how and digital capabilities, ABB helps industries run at high performance while improving efficiency, productivity, and sustainability so they can outperform.We call this ‘Engineered to Outrun’The company has over 140 years of history and more than 105,000 employees worldwide.ABB’s shares are listed on the SIX Swiss Exchange (ABBN) and Nasdaq Stockholm (ABB).At ABB, we are committed to advancing diversity and inclusion across all dimensions: gender, LGBTQ+, abilities, ethnicity, and generations.We welcome and celebrates individual differences to create a future where innovative digital technologies allow greater access to cleaner energy.Your role and responsibilitiesAs part of the People Analytics team, the Data Scientist will contribute to a resourceful, quick-reacting group that supplies dependable, high-quality analytics to business and HR leaders to support Talent, Performance, and Culture planning.Reporting to the Team Lead or Global Head of People Analytics, you will be responsible for delivering global projects that improve workforce decision-making at ABBThe work model for the role is: HybridYou will be mainly accountable for:- Partner with cross-functional and global teams to lead analytics projects that solve complex business problems, managing the end-to-end lifecycle from requirement gathering and data extraction to analysis and presenting insights.- Develop advanced statistical and machine learning models using techniques such as regression, clustering, forecasting, decision trees, neural networks, and other data mining methods to generate actionable insights.- Leverage programming languages and platforms such as Python, R, Snowflake, NoSQL, and data lakes to build predictive models, scalable frameworks, and machine learning solutions.- Translate people and business data into meaningful insights by defining People KPIs and creating impactful visualizations using tools such as Power BI, Advanced Excel, VBA, and other analytics technologies.- Oversee strategic analytics projects focused on workforce performance, cultural development, and employee experience, applying NLP and deep learning techniques to interpret unstructured data and deliver creative outcomes.Qualifications for the role:- Demonstrate initiative, solid quantitative skills, and comfort working with large datasets to extract insights that support strategic decision-making.- Demonstrate programming and coding experience in R, Python, or MS Azure for analytics and data science solutions.- Possess practical experience with Machine Learning, Artificial Intelligence, and Natural Language Processing.- Understand concepts related to SDLC and ETL processes involved in data management and analytics projects.- Demonstrate a high level of skill in recognizing data patterns and crafting persuasive narratives from fragmented or complex datasets.- Experience developing end-to-end decision science solutions including data modeling, ETL, and reporting, with consulting exposure.- Have a Bachelor’s or Master’s degree in Applied Statistics, Mathematics, Engineering, Operations Research, or a related area, along with proficient English communication, quantitative, and technical skills; knowledge of SAP or Workday HCM systems would be beneficialMore about usOur goal in ABB IS (Information Systems) is to leverage information technology to provide valuable, reliable, and competitive IS services for ABB.If you have demonstrable technical skills, a structured mindset, and the motivation to help us stay ahead of the competition, you are the person we are looking for.Building a cleaner, smarter future takes all kinds of minds: the curious, the courageous, and the creative.We welcome people from all backgrounds and experiences.Ready to make an impact?Apply today or visit to learn more about the impact of our solutions across the globe.Recruitment Fraud WarningABB never asks for payment from job applicants.All genuine job offers follow a formal application and interview process.View current job openings and apply at:For more information, read our full fraud warning notice at

Demonstrate initiative, solid quantitative skills, and comfort working with large datasets to extract insights that support strategic decision-making.

• Demonstrate programming and coding experience in R, Python, or MS Azure for analytics and data science solutions.
• Possess practical experience with Machine Learning, Artificial Intelligence, and Natural Language Processing.
• Understand concepts related to SDLC and ETL processes involved in data management and analytics projects.
• Demonstrate a high level of skill in recognizing data patterns and crafting persuasive narratives from fragmented or complex datasets.
• Experience developing end-to-end decision science solutions including data modeling, ETL, and reporting, with consulting exposure.
• Have a Bachelor’s or Master’s degree in Applied Statistics, Mathematics, Engineering, Operations Research, or a related area, along with proficient English communication, quantitative, and technical skills; knowledge of SAP or Workday HCM systems would be beneficial

ABB is a worldwide provider of electrification and automation solutions, enabling a more sustainable and resource-efficient future. By combining its engineering know-how and digital capabilities, ABB helps industries run at high performance while improving efficiency, productivity, and sustainability so they can outperform. We call this ‘Engineered to Outrun’ The company has over 140 years of history and more than 105,000 employees worldwide. ABB’s shares are listed on the SIX Swiss Exchange (ABBN) and Nasdaq Stockholm (ABB). At ABB, we are committed to advancing diversity and inclusion across all dimensions: gender, LGBTQ+, abilities, ethnicity, and generations.