Data Scientist

hace 2 días


distrito federal, México Remobi A tiempo completo

Contract length : 9 months with extensions Location : Remote Role Overview The Senior Data Scientist will support a global data transformation programme focused on improving data quality, discoverability, and monetisation within an industrial spare parts and eCommerce environment. The role combines advanced analytics, machine learning, and business consulting, working closely with technical and non technical stakeholders. Key Responsibilities Collaborate with product owners, engineers, and analysts to identify data driven opportunities Design, build, and deploy machine learning models including classification, clustering, fuzzy matching, and recommendation systems Apply NLP and LLM techniques such as prompt engineering, fine tuning, and embedding based search Conduct discovery sessions to understand business processes, data models, and stakeholder needs Translate business requirements into scalable and measurable data science solutions Support eCommerce initiatives including intelligent search, personalisation, and upselling Participate in agile ceremonies, technical reviews, and stakeholder demonstrations Skills required 3+ years of experience in Python-based data science, including ML modeling and NLP. Proficiency in SQL (e.g., querying Snowflake data warehouse). Excel (for validating results with business). PowerBI or similar BI tools (for descriptive and diagnostic analysis). Data processing in Python, including applying business rules and logic. ML techniques such as classification, clustering, fuzzy matching, and embeddings. LLMs (e.g., OpenAI, HuggingFace), including prompt engineering and fine-tuning. Vector search tools (e.g., FAISS, Pinecone, Weaviate). Cloud platforms (Azure, AWS, GCP), version control (Git), and containerization (Docker). Confident communicator with experience working directly with business stakeholders Experience acting as a bridge between business and technical teams Knowledge of eCommerce, search, or recommendation systems Exposure to industrial, engineering, or asset heavy domains #J-18808-Ljbffr


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