Junior Data Scientist

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The Emerging Tech Standard Delivery Team drives the adoption of advanced technologies and develops enterprise‑ready solutions for D&A Operations. In this role, the individual partners with Operations and Technology teams to design data‑driven solutions that deliver clear business and customer value. The position requires strong expertise in data analytics, NLP, deep learning, and data communication, along with the ability to learn financial content and core D&A business processes. The individual must stay current with emerging technologies and collaborate closely with operations groups and specialized machine learning teams to deliver scalable, high‑impact solutions. Role, Responsibilities & Key Accountabilities: Contribute to the development of data acquisition, cleaning, transformation, and processing workflows as part of the enterprise data management framework. Support the design and improvement of financial analytics data pipelines, helping integrate tools and services to create smooth, end‑to‑end user experiences. Work with analytics domain experts to understand data requirements and translate them into clear tasks, models, or pipeline components under the guidance of senior team members. Assist in implementing data solutions by collaborating with engineering, product, and project delivery teams. Participate in building and evaluating machine learning and deep learning models, including NLP, LLMs, and RAG‑based approaches. Help create evaluation frameworks that measure the effectiveness of automation and AI solutions. Carry out data processing tasks such as web scraping, entity extraction, and pre‑/post‑processing of structured, semi‑structured, and unstructured documents (e.g., PDFs, scanned files). Support cloud‑based development (AWS or similar), including onboarding workloads and following CI/CD and MLOps best practices. Stay current with emerging technologies, analytics techniques, and financial data trends to continually improve your skills. Required Skills: 0-3 years of experience in data science, analytics, or statistical modelling (including internships or academic projects). Foundational knowledge in data analytics, feature engineering, ML, NLP, LLMs, and RAG workflows. Proficiency with Python and familiarity with core data science libraries (Pandas, NumPy, Scikit‑learn, etc.). Experience using Git and exposure to CI/CD pipelines (GitLab/GitHub runners). Understanding of relational databases, statistics, and basic statistical programming concepts. Ability to work with large datasets and perform data cleaning, transformation, and exploratory analysis. Exposure to MLOps fundamentals and experience working with cloud platforms (AWS/Azure). Ability to set and uphold coding standards. Apply AI Agents and human‑AI collaboration frameworks, adopting AI as a productivity amplifier across business functions Understanding Synthetic Data generation techniques to overcome real‑data scarcity, enhance model robustness, and support privacy‑preserving AI development Strong analytical thinking, problem‑solving ability, and prioritization skills. Effective communication skills with the ability to explain technical concepts clearly. Ability to collaborate across teams, take feedback, and contribute to shared goals. Hands-on experience with leading commercial or open-source data management tools. Excellent written, verbal, and presentation skills, with the ability to present to peers, senior management, and cross-functional partners. Broad business awareness and understanding of relevant internal business relationships. Ability to resolve complex business challenges using deep technical knowledge and industry insight. Preferred Exposure to financial services, investment banking, or related domains. Familiarity with Refinitiv or LSEG platforms and datasets. Experience working with distributed or global teams. Education: Master's degree in Statistics, Mathematics, or Computer Science with a Data Science certification, or an Engineering degree specializing in Data Science and Artificial Intelligence. Proficiency in Python, R, and SQL. Career Stage: Senior Associate Compensation Information: LSEG is committed to offering competitive Compensation and Benefits. The anticipated annual gross base salary for this position is between 114,700 zł - 181,500 zł. Please be aware base salary ranges may vary by geographic location. In addition to our offered base salary, this role is eligible for our Annual Bonus Plan ("bonus plan"). Target Bonus % will be commensurate with role level and posted career stage. Individual salary will be reflective of job-related knowledge, skills and equivalent experience. Benefits Information: LSEG roles (excluding internships) are typically eligible for inclusion in our LSEG Benefits program. To view the benefits available for the role you're applying for, please click here . This document provides a list of benefits by country. Simply click on the country where the role is based to vie

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