Data Scientist, VP

In this role as a Data Scientist, you will drive and embed the design and implementation of data science tools and methods to harness data for market-leading customer solutions. You will act as a subject matter expert, articulating advanced data and analytics opportunities through data visualization. If you are ready for a new challenge and keen on using your data science expertise to support external customers, this role at vice president level could be the right fit for you. What you'll do: - Understand the requirements and needs of business stakeholders, form hypotheses, and identify suitable data and analytics solutions to meet their needs and achieve the business strategy. - Maintain external curiosity around new trends in data science, keeping up to date with emerging trends, tooling, and sharing updates within and outside the team. - Proactively bring together statistical, mathematical, machine-learning, and software engineering skills to consider multiple solutions, techniques, and algorithms. - Implement ethically sound models end-to-end, applying software engineering and a product development lens to complex business problems. - Work with and lead direct reports and wider teams in an Agile way within multi-disciplinary data to achieve agreed project and Scrum outcomes. - Use data translation skills to define business questions, problems, or opportunities that can be supported through advanced analytics. - Select, build, train, and test complex machine models, considering model valuation, risk, governance, and ethics throughout to implement and scale models. The skills you'll need: - Evidence of project implementation and work experience in a data-analysis-related field as part of a multi-disciplinary team. - Hold an undergraduate or a master's degree in Data Science, Statistics, Computer Science, or a related field. - 10 years of experience with statistical software, database languages, big data technologies, cloud environments, and machine learning on large data sets. - Ability to demonstrate leadership, self-direction, and a willingness to teach others and learn new techniques. - Experience deploying machine learning models into a production environment. - Proficiency in Python and relevant libraries such as Pandas, NumPy, Scikit-learn, coupled with experience in data visualization tools. - Extensive work experience with AWS Sage maker, including expertise in statistical data analysis, machine learning models, LLMs, and data management principles. - Effective verbal and written communication skills, the ability to adapt communication style to a specific audience, and mentor junior team members.,