Data Science and AI Analyst

Job Description

HPE Operations is our innovative IT services organization. It provides the expertise to advise, integrate, and accelerate our customers’ outcomes from their digital transformation. Our teams collaborate to transform insight into innovation. In today’s fast paced, hybrid IT world, being at business speed means overcoming IT complexity to match the speed of actions to the speed of opportunities. Deploy the right technology to respond quickly to market possibilities. Join us and redefine what’s next for you.

What you’ll do:

Responsibilities:

• Applies basic knowledge of the client’s business need to formulate and define analytic objectives.  Uses available data elements, defines business rules, and solution objectives.
• Develops, enhances and maintains a client’s metadata based on analytic objectives.  May load data into the infrastructure, creates hypothesis matrix, and identifies available data to prepare for the Exploratory Data Anlysis (EDA) and hypotheses.
• Builds models to supports/contribute to the overall solution, validates initial model and validates results & performance after the implementation.
• Researches, identifies, and aids in delivering data science solutions to problem domain. Contributes significantly in measurement of business performance based on the model deployed. If needed, leads the model enhancements.
• Create visualization of the model’s insights for easy consumption.

What you need to bring:

Education and Experience Required:

• Master´s degree in Statistics, Operations Research, Computer Science or equivalent preferred. Or Bachelor´s Degree in these areas and at least 2-3 years of relevant experience.

Knowledge and Skills:

• Data Science and Analyses Proficiency: Expert knowledge of classical methodologies, including regression.
• Generative AI & LLMs: Working knowledge of Generative AI architectures, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
• Advanced Analytics: Proven experience in forecasting, projections, association rules, and sequence analysis to drive business strategy.
• Business Translation: Ability to translate complex business requirements into clear data science objectives and sophisticated mathematical models.
• Programming Expertise: Advanced proficiency in Python and SQL for model development and data manipulation.
• Modern AI Tools: Strong background in utilizing AI/ML frameworks and traditional analytics software (e.g., SAP).
• Data Engineering (ETL): Hands-on experience with data integration, modeling, and ETL tools such as SSIS, Informatica, Ab Initio, or Talend.
• Data Visualization: Mastery of data visualization techniques using Power BI to communicate insights through compelling visual storytelling.
• Global Collaboration: Strong interpersonal skills with the ability to work effectively across geographical boundaries and diverse, cross-functional teams.
• Strategic Communication: Excellent presentation skills, capable of explaining technical data and AI concepts to both technical and non-technical stakeholders.

Additional Skills:

Accountability, Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Bias, Coaching, Creativity, Critical Thinking, Cross-Functional Teamwork, Data Analysis Management, Data Collection Management (Inactive), Data Controls, Design, Design Thinking, Empathy, Follow-Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity (Inactive), Long Term Planning, Managing Ambiguity {+ 5 more}