Data & AI Technical Consultant

w or changed products, services, management of the change process, and professional standards, management of performance of systems and services in relation to their contribution to business performance.

• Environment: Professional knowledge related to incumbent's function/business unit and its processes.

• Communication/Negotiation: Advise other professionals. Effectively use group dynamics. Negotiate to define approaches and goals.

• Problem Solving: Recognize complex problems related to functional objectives. Analyze situations and implement solutions, or develop new system elements, procedures, or processes. Creativity and judgment applied to developmental work on different projects within the business environment.

• Contribution/Leadership: Provides ongoing technical / operational guidance to lead professional work teams, conducts special projects, or manages department(s) (national or international). Understand department/ functional mission and vision. Defines and decides objectives within specified business concept or project and may have responsibility for tools and assigned resources. Utilizes expertise to directly influence people outside department or function.

• Impact on Business/Scope: Accountable for department results and activities and/or projects involving multi-functional teams. Regularly participates in overall functional program planning. Activities are subject to business measurements, impact customer satisfaction, and impact project costs or expenses.

Required Technical and Professional Expertise

• 1 - 2 years of related experience

• IA / Machine Learning Data Science experience - statistical models, machine learning algorithms, Artificial Intelligence. Data Engineering

• Data Management: Understanding of data governance, data quality, and data lifecycle management

• Data Integration: Skills in integrating various data sources, both structured and unstructured, using ETL (Extract, Transform, Load) tools and techniques

• Data Modeling: Ability to create conceptual, logical, and physical data models that align with business requirements

• Big Data Technologies: Familiarity with big data tools like Hadoop, Spark, or NoSQL databases that can handle large volumes of data

• Cloud Computing: Familiarity with cloud platforms (like AWS, Azure, and Google Cloud) as many data fabric solutions are cloud-based

• APIs and Microservices: Understanding of building and consuming APIs and microservices to facilitate data access and integration;

• Analytical Skills: Ability to analyze data and derive insights that can inform business decisions

Preferred Technical and Professional Expertise
As above