Senior Data Scientist

About this role

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Skills you'll use

What you'll do

• Own the product vision for an industry‑leading data management framework, covering data acquisition, cleaning, transformation, and related workflows.
• Support Lead Data Scientist on end-to-end AI/ML lifecycle: problem definition, design, experimentation, deployment, and continuous improvement.
• Define an optimized user experience for financial analytics data pipelines, unifying multiple tools and services into an integrated workflow.
• Partner with analytics domain experts to understand business data needs and translate them into a practical platform and framework strategy.
• Lead the execution of this strategy in close collaboration with engineering and project delivery teams.
• Communicate product goals, progress, and achievements to product, engineering, business leaders, sales, proposition, support, and other internal stakeholders.
• Stay informed on financial analytics market trends to maintain a forward‑looking, future‑ready strategy.
• Continuously learn and adapt to emerging technologies and techniques in financial analytics.
• Develop and deploy production‑grade AI models and data‑driven solutions aligned with strategic objectives.
• Tune and optimize AI models to improve accuracy, performance, and scalability.

Who can apply

• · 6–8 years of experience in data science, analytics, or statistical modelling roles.
• · Strong foundation in data analytics, feature engineering, NLP, predictive modelling, LLMs, and RAG workflows.
• · Expertise in Python and core ML/DL libraries (TensorFlow, PyTorch, Scikit‑learn), with demonstrated experience in developing and productionizing AI models.
• · Proven ability to apply strong statistical analysis skills, including probability and applied statistics, to model development and evaluation.
• · Experience with Git‑based version control and CI/CD pipelines (GitLab/GitHub runners).
• · Strong understanding of relational databases, large‑scale data processing, and statistical programming.
• · Familiarity with MLOps principles and experience deploying solutions on cloud platforms (AWS and/or Azure).
• · Hands‑on experience with commercial or open‑source data management tools.
• · Excellent communication and presentation skills, capable of simplifying complex technical concepts for both technical and business audiences.
• · Strong influencing and collaboration skills, supporting cross‑team execution and alignment.

About LSEG

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