Data Scientist background with 2- 4 years of exp in ML, AI, NLP , LLM , Education - Maths , Stats preferred Data Scientist role is to provide knowledge & support to Refinitiv Data, Product Teams, Development Team and Content Specialist regarding the Company Data content and the Product Generation. Senior Data Scientist will lead the Extraction of data work with content team and Central Tech Standards team on business requirements. Core Responsibilities : - Handle and process large datasets using Python. Define requirements and lead projects to deliver new or enhanced capabilities. Collaborate with business units to see opportunities for improving commercial performance and operational efficiency through data science and analytics. Translate business needs into technical solution requirements. Propose and implement improvements to products and processes. Develop automated and machine learning solutions for sourcing and loading fundamentals data into databases. Build data extraction solutions for various document formats including PDFs, HTML, and XML. Partner with business, content, and product teams to address large-scale analytics problems using efficient resources. Build proof-of-concepts (POCs), visualizations, and pipeline tools for product and development. Work with development teams to deploy analytics solutions. Maintain comprehensive process documentation. Advocate for data science standard methodologies and guide business users and peers on analytical techniques, tools, and technologies. Required Knowledge & Skills : - Strong proficiency in Python programming. Experience with version control systems like Git. Solid grasp of relational databases and SQL. Proficiency in web frameworks such as Flask or Django. Ability to structure and clarify poorly defined problem statements. Familiarity with machine learning algorithms (e.g., Decision Trees, Random Forest). Good understanding of NLP techniques (e.g., Word2Vec, Bag of Words, Embeddings). Experience in crafting, developing, and deploying ML/DL models. Confirmed foundation in statistics and probability. Skilled in libraries such as Scikit-learn, NumPy, and Pandas. Experience with deep learning frameworks like PyTorch or TensorFlow. Proficient in HTML, CSS, and web scraping. Strong analytical thinking and problem-solving skills. Understanding of REST API architecture and containerization tools (Docker/Kubernetes). Ability to handle and analyse large datasets. Capable of storytelling through data analysis and visualization for both technical and non-technical audiences. Excellent written, verbal, and presentation skills for engaging with peers, senior management, and customers. Preferred Qualifications : - Bachelor's/ Professional degree in Engineering, Statistics, Mathematics, Physics or a related quantitative field. Certification in Data Science. Confirmed ability of 5+ years in data science projects, preferably in the finance domain.
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