We are seeking a highly analytical and innovative Data Scientist to develop data models, generate insights, and support data-driven decision-making across the organisation. You will work closely with cross-functional teams to solve complex business problems using statistical analysis, machine learning, and predictive modelling.

• Build predictive, classification, and clustering models using modern machine learning techniques.
• Apply statistical analysis to interpret data patterns and drive business insights.
• Develop algorithms and prototypes to test new hypotheses or concepts.

• Collect, clean, and preprocess structured and unstructured datasets.
• Work with data engineers to enhance pipelines, ETL processes, and data quality.
• Implement feature engineering, model validation, and performance optimization.

• Translate complex data findings into actionable insights.
• Present clear recommendations to stakeholders, product teams, and management.
• Collaborate with business units to define KPIs, experiments, and analytical frameworks.

• Deploy machine learning models into production environments when required.
• Monitor model performance, accuracy, and effectiveness over time.
• Continuously refine and improve algorithms and analytical approaches.

• Partner with product, engineering, marketing, and operations teams to solve business challenges.
• Contribute to experimentation design (A/B testing, statistical testing).
• Support data governance, documentation, and best practices.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field.
• 2–5 years of experience in data science, machine learning, or advanced analytics.
• Strong proficiency in Python or R (e.g., pandas, scikit-learn, TensorFlow, PyTorch).
• Solid foundation in statistics, probability, and machine learning concepts.
• Experience working with SQL and large datasets.
• Familiarity with cloud platforms (AWS, Azure, GCP) is a plus.
• Strong communication and ability to translate data findings into business insights.
• Excellent problem-solving skills and attention to detail.

• Experience with deep learning, NLP, or computer vision.
• Familiarity with big data tools (Spark, Databricks, Hadoop).
• Knowledge of MLOps tools and CI/CD processes.
• Experience with BI tools (Tableau, Power BI).
• Background in experiment design and causal inference.

• Opportunity to work with modern data stacks and machine learning technologies.
• Career growth pathways (Senior Data Scientist, Lead Data Scientist, ML Engineer).
• Collaborative and supportive data-driven environment.
• Access to training, certifications, and continuous learning.
• Competitive salary and benefits package.