GenAI Data Scientist

Nextlink is looking for a hands-on GenAI Data Scientist to join the Data Analytics & Foundational Platforms team within Wealth Management Americas. The role focuses on designing, developing, evaluating, and deploying Generative AI and machine learning solutions that enhance business decision-making, automate workflows, and improve operational efficiency.

The ideal candidate will have strong programming and analytical skills, practical experience building AI/ML applications, and the ability to translate business requirements into scalable, reliable, and production-ready solutions.

Key Responsibilities

• Design, develop, test, and deploy Generative AI and machine learning solutions in collaboration with senior data scientists and technical leads.
  
• Build AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), semantic search, embeddings, and agent-based architectures.
  
• Develop and maintain evaluation frameworks to assess the accuracy, reliability, consistency, and performance of LLM-based applications.
  
• Prepare, process, and analyze structured and unstructured data for machine learning and AI application development.
  
• Experiment with prompt engineering, retrieval strategies, model configurations, embeddings, and fine-tuning techniques to optimize solution performance.
  
• Develop, validate, and implement machine learning models using techniques such as classification, clustering, and optimization.
  
• Write clean, reusable, maintainable Python code following software engineering, version control, testing, and reproducibility best practices.
  
• Develop Power BI dashboards and visualizations to communicate analytical insights and support business decision-making.
  
• Work with SQL databases to extract, transform, validate, and prepare data for analytical and machine learning use cases.
  
• Monitor production AI applications, investigate issues, perform root-cause analysis, and continuously improve solution quality and performance.
  
• Collaborate with business stakeholders, product managers, data scientists, and technology teams to translate business requirements into effective technical solutions.
  
• Document methodologies, experiments, model performance, technical decisions, and implementation outcomes.
  
• Ensure responsible AI practices, output validation, compliance with organizational policies, and adherence to applicable risk and governance standards.
  

Required Skills and Qualifications

• Strong hands-on programming experience in Python, including familiarity with commonly used data science and machine learning libraries.
  
• Practical experience developing or prototyping Generative AI applications using LLMs.
  
• Understanding of Natural Language Processing (NLP), deep learning, machine learning, and agentic AI systems.
  
• Hands-on knowledge of RAG pipelines, prompt engineering, embeddings, vector search, semantic retrieval, and information retrieval systems.
  
• Experience evaluating machine learning models or LLM-based applications using appropriate performance and quality metrics.
  
• Strong SQL skills and experience working with structured data, databases, and analytical data preparation.
  
• Mandatory hands-on experience in Power BI, including dashboard development and data visualization.
  
• Familiarity with machine learning techniques such as classification, clustering, and optimization.
  
• Exposure to cloud and data platforms such as Microsoft Azure, AWS, GCP, or Databricks.
  
• Familiarity with Git, version control, code reviews, automated testing, and software development best practices.
  
• Strong analytical, problem-solving, communication, and stakeholder-management skills.
  
• Ability to work collaboratively in a fast-paced environment and deliver practical, business-focused solutions.
  
• Bachelor's or master's degree in Computer Science, Data Science, Machine Learning, Statistics, Computational Linguistics, or a related quantitative discipline.
  

Preferred Technical Skills

Experience with one or more of the following technologies and frameworks is preferred:

• GenAI and LLMs: Azure OpenAI, Anthropic APIs, OpenAI SDKs.
  
• AI/ML frameworks: PyTorch, Hugging Face Transformers, spaCy.
  
• LLM orchestration: LangChain, LangGraph, or equivalent frameworks.
  
• LLM evaluation: DeepEval or comparable evaluation frameworks.
  
• Data and analytics platforms: PostgreSQL, Greenplum, Hadoop, Databricks, or similar technologies.
  
• Business intelligence: Power BI and Tableau.
  

Preferred Experience

• Prior experience in financial services, banking, wealth management, or investment management.
  
• Experience developing enterprise search, question-answering, document intelligence, or AI-assisted workflow automation solutions.
  
• Exposure to productionizing and monitoring AI/ML applications in cloud environments.