Data Science Professional

What you’ll be doing 1.Supports the implementation of technical solutions for customers and colleagues, working within cross-functional squads to assist in creating and implementing technical solutions for a domain or cross domain activity within a specific technology area.2.Supports in the execution of technical decisions, technology choices and architecture for a wide range of high-performance products, capabilities, and platforms effectively balancing short-term impact with long-term transformation.3.Supports the design and development of software solutions aligned to architecture and security standards.4.Undertakes technical reviews to maintain proficiency in software engineering principles and practices.5.Supports with the designs of technical specifications and development of software solutions of smaller and /or less complex initiatives in partnership with team, contributing towards the quality of delivery.6.Writes, tests and reviews code under supervision, refining as needed and communicates to engineering professionals and colleagues involved in the project.7.Integrates existing software products and resolves routine compatibility issues.8.Maintains systems by monitoring and correcting software defects.9.Supports the implementation and maintenance of high-quality tools and automation processes to support continuous delivery and developer productivity.10.Supports the use of tools and automation processes to enable continuous delivery.11.Contributes to the delivery of technical roadmaps aligned to business and engineering needs.12.May support engineering and operational excellence initiatives, assisting with implementing metrics and processes for regular assessment and improvement.13.Supports in the implementation of ways to improve working processes within the area of software engineering responsibility. The skills you’ll need to succeed • ML & AI: Applies knowledge of artificial intelligence and machine learning from a data perspective and understands potential data applications to improve overall business outcomes. (Tech stack (AWS/GCP & Hadoop), spark, python, SQL, cloud native services). • Statistical Analysis: Uses mathematical models to quantify relationships between data points and make predictions. • Data Management: Understanding of data governance, data quality, and data privacy standards. • Data Modelling: Ability to design and implement effective data models to support business processes. • Storytelling with data: skills in building the case for change, drawing on data and analytical techniques where appropriate, and communicating this to business audiences • Data Cleansing: ensures data quality checks are built into analytics process to assure clean data. • Dashboards: Strong experience in Dashboard build inc. Qlik Experience you’d be expected to have Have at least 3+ years of experience in end-to-end machine learning deployments and maintenance of deployed solutions. Our leadership standards Looking in: Leading inclusively and Safely I inspire and build trust through self-awareness, honesty and integrity.Owning outcomes I take the right decisions that benefit the broader organisation. Looking out: Delivering for the customer I execute brilliantly on clear priorities that add value to our customers and the wider business.Commercially savvy I demonstrate strong commercial focus, bringing an external perspective to decision-making. Looking to the future: Growth mindset I experiment and identify opportunities for growth for both myself and the organisation.Building for the future I build diverse future-ready teams where all individuals can be at their best.