01Overview
Job Description
We are seeking a talented Data Scientist with competency in Data Engineering capabilities to design, build, and deploy some advanced analytical solutions across a range of environmental sectors. This role is ideal for a skilled who can develop machine learning models, support the engineering of robust data pipelines, and contribute to the broader technical architecture.
The successful candidate will be able to apply analytical techniques, work with complex and large-scale datasets, collaborate with cross-functional teams, and support the development of high-quality data infrastructure enabling reliable, scalable data-driven decision-making.
Responsibilities
Data Science & Advanced Analytics
Build, validate, and deploy sophisticated predictive and statistical models using up-to-date Python-based libraries. (e.g., scikit-learn, TensorFlow, PyTorch)
Conduct exploratory data analysis, statistical modelling, hypothesis testing, and insight generation to support strategic business decisions.
Develop high-quality, interpretable data visualisations using Matplotlib, Seaborn, and similar tools.
Translate complex analytical outcomes into explicit, actionable insights for both technical and non-technical stakeholders.
Data Engineering & Pipeline Development
Design and implement robust, scalable data orchestration pipelines using tools such as Airflow or Dagster.
Work with big data technologies (Spark, Hadoop, Dask) to process and analyse large-scale datasets efficiently.
Define and implement data models using ER diagrams, normalisation techniques (e.g., star schema, Snowflake), and modern ORM frameworks (e.g., SQLAlchemy).
Provision, administer, and optimise relational databases, including schema design, indexing, and access management.
Build high-performance APIs using frameworks such as FastAPI or Flask, following best RESTful design practices.
Software Engineering and DevOps Integration
Develop modular, maintainable, object-oriented Python code using .
