Data Scientist / Machine Learning Engineer

Job Description

Responsible for supporting the delivery of business analysis and consulting processes and procedures for the defined specialism using basic technical capabilities, developing working relationships to provide support with queries, issues and ad-hoc requests and assisting with quality assurance services. Specialisms: Business Analysis; Data Management and Data Science; Digital Innovation. You will work with The AppSim team is responsible for driving application simplification across the organization, focusing on reducing operational complexity and technical debt. They work closely with the wider digital delivery and digital core teams to identify and pursue simplification opportunities. The team collaborates with business partners to align simplification efforts with broader transformation goals and drive measurable improvements in operational efficiency. Let me tell you about the role A data scientist applies scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data Their key responsibilities include gathering and analyzing large sets of data, using machine learning algorithms, statistical models, and data processing techniques to predict future trends and provide actionable insights A machine learning engineer designs and develops artificial intelligence ( AI ) systems that can learn and make decisions autonomously Their key responsibilities include creating and optimizing machine learning models, developing algorithms that enable machines to perform tasks without explicit programming, and working with large datasets to train these models They collaborate with data scientists, software engineers, and domain authorities to implement machine learning solutions that address specific business needs Additionally, machine learning engineers are responsible for ensuring the scalability and efficiency of machine learning systems, continuously improving model performance through rigorous testing and validation, and staying updated with the latest advancements in the field to integrate pioneering techniques into their work What you will deliver As part of a cross-disciplinary team in AppSim, you will collaborate closely with data scientists, data engineers, software engineers, data managers, and business partners to build scalable, reusable data science products that drive application simplification. You will apply statistical and machine learning algorithms, carry out data analyses to provide actionable business insights, and drive best practices in technical design, unit testing, code review, and documentation. Additionally, you will present your results to peers and senior management, actively contribute to improving developer velocity, and mentor others within the team. What you will need to be successful (experience and qualifications) Essential MSc or PhD degree in a quantitative field or equivalent. Hands-on experience crafting, planning, prototyping, productionizing, maintaining and detailing reliable and scalable data science products in sophisticatedin environments. Applied knowledge in a team (if not leading) of data science tools and approaches across all data lifecycle stages. Detailed understanding of underlying mathematical foundations of statistics and machine learning. Development experience in one or more object-oriented programming languages (eg Python, Go, Java, C++) Basic SQL knowledge. Customer-centric and pragmatic approach. Focus on value delivery and swift execution, while maintaining attention to detail. Strong customer management and ability to lead large organizations through influence. Continuous learning and improvement attitude. Desired Experience with big data technologies (eg Hadoop, Hive, and Spark) is a plus. Knowledge of experimental design and analysis is a plus. No prior experience in the energy industry required. Travel Requirement Up to 10% travel should be expected with this role Skills: AI Systems, Business Acumen, Data Cleansing, Data Preparation, Machine Learning, Python Automation, Solutions Design, SQL Databases