Data Scientist

Data scientists use statistical methods to collect and organize data. Problem-solving skills. Data scientists must devise solutions to the problems they encounter in data collection and cleaning and in developing statistical models and algorithms.

- Supports projects, leveraging technical expertise to remove obstacles and to find creative solutions.

- Builds data science products and solutions utilising data science techniques directly.

- Creates compelling proposals with technologists and business to drive innovation from conception to production with appropriate success metrics.

- Builds and uses domain expertise in financial market content, data science and LSEG data and products.

- Writes highly optimised code for LSEG products and solutions

Problem Solving - Defines a problem, generates solutions, and evaluates and identifies the best solution to overcome the problem

Artificial Intelligence Ethics - Demonstrates knowledge and application of moral principles, guidelines and techniques to inform the development and responsible use of artificial intelligence technology.

Programming - Develops and implements various sets of instructions, using specific programming languages, to enable a computer to do a certain task. Examples of programming languages include: C++, Python

Data Analysis - Collects, analyses and interprets data to reach conclusions and/or present insights and findings.

Data Wrangling - Cleans, manipulates and transforms data from one form into another format that is more useful and valuable

Statistics - Applies the right statistical methods or formulas to solve problems or analyse a situation

Algorithms - Understands and uses algorithms to gather insights from data

Communication - Communicates with clarity and precision, presenting complex / technical information in a concise format that is audience appropriate

Negotiation & influence - Engages in discussion to reach an agreement and create outcomes, affecting the action, behaviours, or opinions of others

Translating business requirements - Understands what the customers, end-users and business needs are from the business requirements and translates this into technical specifications, solutions and products.

Interpreting & critiquing results and publications - Demonstrates subject matter expertise by interpreting and critiquing results and publications

Research - Investigates information systematically, asks inquisitive questions, and studies materials and sources to reach new conclusions and / or create new ideas, methods, products or solutions.

Metrics creation - Develops, implements, and monitors key performance indicators and metrics.