Senior Data Scientist (ML/GenAI)

We are seeking a Senior Data Scientist with a strong background in AI, machine learning, and data-driven decision-making to develop and optimize predictive models, generative AI solutions, and large language model (LLM) applications. This role requires close collaboration with business leaders, product teams, and software engineers to design and implement cutting-edge AI solutions that drive actionable insights and automation.

The ideal candidate will have practical experience in AI model development, large-scale data processing, and advanced statistical analysis. A deep understanding of machine learning fundamentals, including deep learning, regression, classification, clustering, and retrieval-augmented generation (RAG) techniques, is essential. The role may also require rapid adaptation to emerging technologies, supported by a strong foundation in AI/ML principles and hands-on programming skills.

• Develop and deploy AI/ML models that enhance business insights, automation, and predictive capabilities.

• Collaborate with business and product teams to identify AI-driven opportunities and translate data insights into impactful solutions.

• Conduct rigorous data experiments using advanced machine learning techniques to drive incremental improvements.

• Design, implement, and optimize data pipelines, ensuring efficient data transformation, feature engineering, and model deployment.

• Deliver data-driven reports and presentations, effectively communicating complex AI concepts and findings to both technical and non-technical stakeholders.

• Work closely with software engineers and developers to integrate AI solutions into scalable production systems.

• Continuously evaluate and refine AI/ML models, ensuring alignment with industry best practices and technological advancements.

• 3+ years of experience in a data science or AI/ML engineering role.

• PhD or Master's degree in Computer Science, Machine Learning, AI, or a related field (or equivalent industry experience in designing and evaluating ML systems).

• Proficiency in machine learning frameworks such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or equivalents.

• Strong foundation in statistical analysis, including hypothesis testing and data modeling.

• Expertise in programming languages (e.g., Python, R, SQL) for AI model development and data manipulation.

• Hands-on experience with data visualization tools to create meaningful insights.

• Practical knowledge of LLM-based pipelines, including retrieval-augmented generation (RAG) and prompting techniques.

• Familiarity with emerging AI/ML tools, such as LangChain, LlamaIndex, Haystack, Azure AI Studio, and vector databases.

• Experience handling databases and data management systems, including SQL, Azure Data Factory, Hadoop, or Spark.

• Understanding of MLOps fundamentals, including orchestration tools, cloud compute infrastructure, and observability frameworks.

• Knowledge of best software development practices, including Continuous Integration (CI/CD), unit testing, and code reviews.

• Ability to work independently and in a collaborative, fast-paced environment.

• Experience in financial services, revenue cycle management, or collections is a plus but not required.

• Familiarity with big data frameworks (Hadoop, Spark) for large-scale data processing.

• Prior experience in cloud-based AI deployments on Azure, AWS, or GCP.

• 5 to 7 years of industry experience in AI, data science, or ML engineering.

• Postgraduate degree (MSc/PhD) or equivalent work experience in AI/ML model development and deployment.