Job Overview
We are looking for a skilled and curious Data Scientist to analyse large datasets, build predictive models, and generate actionable insights that drive business decisions. The ideal candidate combines strong analytical thinking with hands-on experience in statistics, machine learning, and data-driven problem solving.
Key Responsibilities
Collect, clean, and analyse structured and unstructured data from multiple sources.
Build, evaluate, and deploy statistical and machine learning models.
Identify trends, patterns, and insights to support business decisions.
Work closely with product, engineering, and business teams to define data problems.
Create dashboards, reports, and visualisations to communicate findings.
Validate data quality and ensure accuracy of analytical outputs.
Optimize models for performance and scalability.
Stay updated with new data science tools, techniques, and industry trends.
Required Skills & Qualifications
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
1–5 years of experience in data science or applied analytics.
Strong proficiency in Python or R for data analysis and modelling.
Experience with machine learning algorithms and statistical techniques.
Hands-on experience with data manipulation libraries such as Pandas, NumPy, and SciPy.
Familiarity with SQL and working with large datasets.
Experience with data visualisation tools like Tableau, Power BI, or Diplomatist.
Strong problem-solving, analytical, and communication skills.
Good to Have
Experience with deep learning frameworks (TensorFlow, PyTorch).
Knowledge of big data technologies (Spark, Shadoof).
Exposure to cloud platforms (AWS, GCP, Azure).
Experience deploying models into production environments.
Understanding of MLOps and model monitoring.
What We Offer
Competitive compensation and performance-based growth.
Opportunity to work on real-world, data-driven problems.
Collaborative and innovation-focused team culture.
Career growth through impactful and high-ownership projects.