Data Scientist

🌟 We're Hiring: Data Scientist! 🌟

Job Description

We are looking for a Data Scientist to analyse large and complex operational and transactional datasets, develop machine learning models, and translate business problems into actionable analytical solutions. The role involves applying statistical techniques, building data pipelines, and deploying models into production to support operational decision-making and business outcomes.

Key Responsibilities

• Analyse large, complex, and unstructured operational or transactional datasets to identify patterns, trends, and insights.
• Translate business and operational challenges into analytical problems and select appropriate statistical and machine learning techniques.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
• Develop, evaluate, and optimise machine learning models using techniques such as anomaly detection, classification, clustering, and risk modelling.
• Assess model performance, evaluate trade-offs, and communicate findings and recommendations to non-technical stakeholders.
• Build and maintain data pipelines to support analytics and machine learning workflows.
• Deploy models beyond experimentation into production environments and support their ongoing use in operational processes.
• Apply software engineering practices, including Git, automated testing, and API integration.
• Collaborate with engineers, product teams, and domain experts to deliver practical data science solutions.
• Take ownership of analytical solutions and ensure that insights and models are effectively integrated into operational workflows.

Job Requirements

• Degree in Data Science, Computer Science, Statistics, Machine Learning, Data Analytics, Information Systems, or a related field.
• Experience working with large, complex operational or transactional datasets.
• Practical experience in applied data science, including statistics, feature engineering, machine learning, and model evaluation.
• Experience with anomaly detection, classification, clustering, risk modelling, or related analytical techniques.
• Strong proficiency in Python and SQL.
• Experience building data pipelines and deploying machine learning models into production environments.
• Familiarity with software engineering practices, including Git, automated testing, and APIs.
• Ability to translate business requirements into analytical solutions and explain technical findings clearly to non-technical stakeholders.
• Ability to work independently in an ambiguous, fast-paced environment while collaborating with cross-functional teams.

Preferred Skills

• Experience with containers and containerisation technologies.
• Familiarity with CI/CD pipelines and DevOps practices.
• Exposure to ModelOps or machine learning model deployment and management practices.

Key Skills

Python, SQL, Data Science, Statistics, Machine Learning, Feature Engineering, Anomaly Detection, Classification, Clustering, Risk Modelling, Model Evaluation, Data Analysis, Data Pipelines, Model Deployment, Git, Automated Testing, APIs, CI/CD, DevOps, ModelOps.

Eager to shape the future with data? 🚀 Apply now and join us on this exciting journey!