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Data Scientist
Job Location:
Monthly Salary:
Posted:
4 November 2026 (6 hours ago)
Posted:
Application Deadline:
1 February 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
About Ambee
Ambee is building climate intelligence. We combine proprietary on-ground sensor data satellite and earth observation data and advanced data science to produce hyperlocal insights on air quality pollen weather wildfire and more. Businesses and organisations use this intelligence through our APIs and platforms to understand environmental risk and make better decisions. Behind it are data systems that process massive volumes of data every day so scale accuracy and reliability are core to everything we build.
About the role
Were hiring a Data Scientist to build the models and analytics behind Ambees climate intelligence products. Youll turn sensor readings satellite imagery and weather data into accurate hyperlocal predictions for air quality pollen weather and wildfire risk. Youll own problems end to end from exploring raw data and engineering features to training validating and shipping models that power the APIs our customers rely on every day. The work involves large spatio-temporal datasets noisy real-world signals and models that must hold up in production. Youll work closely with engineering product and domain experts and help shape how data science is done at Ambee.
What youll do
- Work with stakeholders to frame business and scientific questions as well-defined data science problems with clear success metrics.
- Build train and validate statistical and machine learning models for forecasting nowcasting spatial interpolation and anomaly detection across environmental data.
- Combine and clean data from ground sensors satellites weather models and third-party sources handling gaps drift outliers and calibration issues.
- Engineer features from large spatio-temporal datasets including time series geospatial rasters and point data.
- Design rigorous evaluation: backtesting cross-validation error analysis and comparison against ground truth.
- Work with engineering to deploy models to production and monitor their accuracy drift and cost over time.
- Run exploratory analyses and experiments and turn findings into clear recommendations for product and business teams.
- Build reusable pipelines notebooks and tooling that make the teams work reproducible and faster.
- Stay current with research in machine learning remote sensing and climate science and bring the best ideas into our products.
- Document methods and results so engineers and non-technical stakeholders can understand and trust them.
What youll need
- Bachelors or Masters degree in Engineering in Computer Science or a degree in a relevant field such as Statistics Mathematics Physics Data Science Atmospheric or Environmental Science.
- 1 years of professional experience in data science or applied machine learning.
- Strong foundations in statistics probability linear algebra and machine learning.
- Strong Python skills and hands-on experience with pandas NumPy scikit-learn and at least one deep learning framework such as PyTorch or TensorFlow.
- Experience with time series forecasting and modelling using classical methods (ARIMA state space models) and ML approaches (gradient boosting neural networks).
- Good SQL skills and experience working with relational or NoSQL databases.
- Experience taking models from prototype to production working with engineers on APIs monitoring and retraining.
- Experience working with large messy real-world datasets and turning them into reliable insights including optimising code queries and memory use for speed and scale (vectorisation chunking partitioning efficient formats like Parquet).
- Ability to design sound experiments and evaluate models honestly including uncertainty and failure cases.
- Familiarity with Git code reviews and writing clean tested reproducible code.
- Clear communication of complex results to technical and non-technical audiences.
Good to have
- Experience with big data technologies such as Apache Spark Databricks Hadoop Dask or Kafka and processing datasets that dont fit on a single machine.
- Experience building data pipelines (ETL/ELT batch or streaming) with tools like Airflow or similar orchestrators.
- Experience with geospatial and remote sensing data (GeoPandas xarray rasterio GDAL NetCDF GRIB) and satellite products.
- Background in atmospheric science meteorology air quality hydrology or other environmental domains.
- Experience with cloud platforms especially AWS (S3 SageMaker EMR Athena Lambda).
- MLOps exposure including MLflow Docker model registries CI/CD for models and observability.
- Experience with LLMs and generative AI frameworks (for example LangChain LlamaIndex OpenAI or Anthropic APIs vector databases).
- Publications Kaggle results or open-source contributions in relevant areas.
Who you are
- You work independently. You take open-ended problems break them down and drive them to a shipped model with little supervision.
- Youre rigorous. You question your data test your assumptions and care about whether a model is actually right not just whether the metric looks good.
- You think about production from day one: accuracy latency cost and how a model behaves when the data changes.
- You communicate clearly with engineers scientists and business stakeholders alike.
- Youre driven by the impact of your work love digging into hard problems and are always keen to learn something new.
Why join Ambee
- Work on real-world problems with large environmental datasets from sensors satellites and weather models used by customers worldwide.
- Build models that help people and businesses respond to climate risks.
- High ownership a small and fast-moving team and room to grow into technical leadership.
- Exposure to data engineering AI/ML and cloud infrastructure alongside core product work.
Not quite this role
Were always looking for people who bring new perspectives curiosity and fearlessness to our work. Write to us at with the role you have in mind and well get in touch.
Required Experience:
IC
About Company
Get accurate climate & environmental data to drive business growth. Mitigate climate change risks using our data on pollen, air quality, weather, and more.
