Data Scientist

• Collaborate with business stakeholders, product managers, and engineering teams to translate business requirements into analytical solutions.
• Extract and integrate data from multiple sources through APIs, databases, and file-based interfaces.
• Analyse structured and unstructured data to identify trends, patterns, and actionable business insights.
• Perform data preprocessing, feature engineering, model development, deployment and model evaluation
• Evaluate, fine-tune, and optimise AI/ML models to improve accuracy, performance, scalability, and reliability.
• Develop APIs and services for model deployment and integration with enterprise systems.
• Ensure data quality, governance, security, and compliance throughout the analytics lifecycle.
• Stay current with emerging AI, GenAI, machine learning, and data science technologies and recommend their adoption where appropriate.

Client is looking to hire a talented Data Scientist with 5 to 8 years of experience to join our team and develop high-impact, scalable predictive analytics solutions. You will leverage advanced Gen AI and AI/ML to build solutions, build data pipelines, and be part of the productisation team responsible for delivering robust solutions for our clients., * Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.

• 5 to 8 years of hands-on experience in Data Science, Machine Learning, and Predictive Analytics.
• Strong proficiency in Python, including experience with data manipulation, statistical analysis, machine learning, and model development using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch and related frameworks.
• Solid understanding of statistics, probability theory, hypothesis testing, regression analysis, sampling techniques, and experimental design to support data-driven decision-making.
• Apply statistical and machine learning techniques to analyse large datasets, identify patterns, build predictive models, and generate actionable business insights.
• Experience with Generative AI technologies, Large Language Models (LLMs).
• Experience working with SQL and NoSQL databases, data warehouses, and big data technologies.
• Familiarity with cloud platforms such as AWS and containerization technologies such as Docker and Kubernetes.
• Experience in building REST APIs and integrating AI models into production environments.
• Strong understanding of statistics, machine learning algorithms, forecasting techniques, and optimisation methods.
• Excellent analytical, problem-solving, and communication skills with the ability to work in cross-functional teams., * Experience using graph technologies such as Neo4j and graph data modelling for fraud detection, relationship analysis, or customer intelligence.
• Familiarity with data governance and data quality frameworks.
• Exposure to statistical methods and techniques for entity matching and identity resolution.