Senior Data Analyst

About Our Data Analytics Team:

We are passionate about transforming data into actionable insights, driving strategic decisions and innovation across the organisation. As we continue to grow, we seek a highly skilled and motivated Data Scientist to shape the future of data-driven solutions.

Job Overview:

The Data Scientist will play a pivotal role in building, refining, and deploying advanced models that empower the business with predictive and prescriptive insights. You will collaborate with data engineers, stakeholders, and fellow data scientists to deliver projects from ideation through to production deployment.

Main Responsibilities:

• Model Building: Design and develop robust machine learning and statistical models tailored to solving complex business problems. Select appropriate algorithms, optimise parameters, and rigorously validate models to ensure high performance and reliability.
• Model Refinement: Continuously monitor, test, and improve models based on feedback, new data, or changing business requirements. Implement techniques such as hyperparameter tuning, feature engineering, and cross-validation to enhance model accuracy and generalizability.
• Model Deployment: Deploy models to production environments, ensuring scalability, stability, and maintainability. Work closely with data engineers and DevOps teams to integrate models into business systems, APIs, or real-time applications.
• Data Analysis & Exploration: Analyse large and complex datasets to uncover trends, patterns, and opportunities. Use statistical methods to interpret results and present actionable recommendations to stakeholders.
• Collaboration & Communication: Work cross-functionally with stakeholders, product managers, analysts, and engineers to understand requirements, translate business needs into analytical solutions, and clearly communicate findings and recommendations.
• Documentation & Best Practices: Maintain comprehensive documentation for models, codebases, and analytical processes. Promote and adhere to best practices in coding, experimentation, and reproducibility.
• Innovation & Learning: Stay abreast of the latest developments in data science, machine learning, and AI. Proactively identify and evaluate new tools, frameworks, and techniques that can enhance our capabilities.

Required Skills and Qualifications:

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, Engineering, or a related field. PhD is a plus.
• Proven experience (3+ years) in building, refining, and deploying machine learning/statistical models in a professional setting.
• Strong programming skills in Python, R, or similar languages, with proficiency in machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
• Solid understanding of data structures, algorithms, and software engineering principles.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and model deployment tools (e.g., Docker, Kubernetes, MLflow) is highly desirable.
• Familiarity with big data technologies (e.g., Spark, Hadoop) and database systems (SQL/NoSQL).
• Strong grasp of statistical concepts, hypothesis testing, and experimental design.
• Excellent problem-solving skills, with the ability to break down complex issues into actionable tasks.
• Outstanding communication skills, with the ability to convey complex technical concepts to non-technical audiences.
• Demonstrated ability to thrive in a collaborative, fast-paced environment.

Benefits:

• Opportunity to work with cutting-edge technologies and tools
• Collaborative and dynamic work environment
• Professional development and growth opportunities

Others:

• We value diversity, equity, and inclusion in the workplace
• We offer flexible working arrangements and a healthy work-life balance
• We are committed to continuous learning and improvement