Atos is a global leader in digital transformation with 110,000 employees in 73 countries and annual revenue of € 12 billion. European number one in Cloud, Cybersecurity and High-Performance Computing, the Group provides end-to-end Orchestrated Hybrid Cloud, Big Data, Business Applications and Digital Workplace solutions. The Group is the Worldwide Information Technology Partner for the Olympic & Paralympic Games and operates under the brands Atos, Atos|Syntel, and Unify. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index.
The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space.
We are looking for a Data Scientist who will support our digital workplace operations, innovation, leadership, and engineering teams with insights gained from analyzing our data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the efficiency of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/crafting algorithms and crafting/running simulations. They must have a validated ability to drive business results with their data-based insights. They must be comfortable working with a wide range of partners and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with partners to improve business outcomes. This position will report to the office of the Digital Workplace Chief Innovation Officer.
· Work with partners throughout the organization to find opportunities for demonstrating company data to drive business solutions.
· Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
· Assess the effectiveness and accuracy of new data sources and data gathering techniques.
· Develop custom data models and algorithms to apply to data sets.
· Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
· Develop company A/B testing framework and test model quality.
· Coordinate with different functional teams to implement models and monitor outcomes.
· Develop processes and tools to monitor and analyze model performance and data accuracy.
· Have a Master’s or PHD in Statistics
· Have 5 to 7 years of validated experience manipulating data sets and building statistical models, has a Mathematics, Computer Science or another quantitative field.
· Be able to work from home efficient with a distributed team
· Strong problem-solving skills with an emphasis on product development.
· Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.
· Experience working with and crafting data architectures.
· Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
· Knowledge of sophisticated statistical techniques and concepts (regression, properties of distributions, statistical tests and accurate usage, etc.) and experience with applications.
· Excellent written and verbal communication skills for coordinating across teams.
· An aim to learn and master new technologies and techniques.
Understanding with the following software/tools:
· Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining
· Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
· Experience using web services: Looker, Microsoft DAX, Python, Google BigQuery and AWS Redshift, ML, ServiceNow.
· Practical experience building and distributing advanced PowerBI templates interfaced to Google Big Query
· Experience crafting and using sophisticated machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
· Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Here at Atos, we want all of our employees to feel valued, appreciated, and free to be who they are at work. Our employee lifecycle processes are designed to prevent discrimination against our people regardless of gender identity or expression, sexual orientation, religion, ethnicity, age, neurodiversity, disability status, citizenship, or any other aspect which makes them unique. Across the globe, we have created a variety of programs to embed our Atos culture of inclusivity, and work hard to ensure that all of our employees have an equal opportunity to contribute and feel that they are exactly where they belong.