🎯 Role: Data Scientist / ML Analyst
📍 Location: Flexible / Remote options available
📅 Experience: 4–6 years in analytics, ML, or data science roles
🔍 Overview
We’re seeking a curious and strategic analytics professional — someone who can go beyond answering immediate business questions and proactively generate deeper insights and value from data. You’ll need a strong understanding of machine learning algorithms, belief in their practical use, and the ability to deploy code in a language-agnostic ML environment.
🛠️ Responsibilities
- Deliver timely and reliable business insights using a range of tools and frameworks, across various tech stacks (including open-source environments)
- Collaborate closely with software and data engineering teams to ensure models and insights are robust, scalable, and production-ready
- Build and communicate compelling data narratives through dashboards and visual tools such as Tableau, Power BI, Streamlit, or similar
- Write high-quality, efficient code in Python and R, with strong working knowledge of SQL and Excel; additional languages like Java, Scala, or Julia are welcome
- Handle the full data workflow — from sourcing and cleaning, to manipulating and analysing large datasets
- Apply machine learning techniques including regression, forecasting, classification, NLP, decision trees, and search algorithms
📚 Requirements
- 4–6 years of relevant experience in delivering data products and deploying ML models within live data pipelines
- Strong grasp of reproducible data science practices, including insight generation, feature engineering, and validation techniques
- Experience in interpretability and causal inference is a plus
- Comfortable turning data insights into visual and verbal stories for a range of business audiences
- Degree in a quantitative field (e.g. Mathematics, Statistics, Computer Science, Engineering, or similar); postgraduate education is beneficial but not mandatory
