• Optimize functionality and scalability of data science prototypes by iteratively experimenting with different algorithms, train and fine-tune parameters/hyper-parameters while maintaining desired quality measures
• Proficiency in AI/machine learning (ML) frameworks and libraries to verify data quality, train, assess and deploy machine learning AI/ML models
• Perform statistical tests to assess model performance, robustness and reliability (e.g. recall, precision, F1 scores etc.). Experience in training/re-training models when necessary
• Familiarity with distributed data stores and parallel processing that can handle/augment large scale data processing and analysis
• Development/use of APIs to connect the outputs of AI/ML models with business intelligence platforms/graphical interfaces
• Extensive documentation of artificial intelligence/machine learning processes detailing the complete workflow from data gathering to pre-processing to model training and deployment
• Contribution to and maintenance of data science/data transformation infrastructure (data warehouses/data lakes etc.)

Requirements

• A minimum of a bachelor’s degree (master’s degree will be an advantage) in mathematics, data science, computer science or a related field
• Previous work experience as a statistician/data scientist/computer scientist is preferable
• Proficiency in programming languages in R, Python, Java, Matlab etc.
• Prior experience in handling/managing various data types and formats (remote sensing, surveys, text data etc.)
• Demonstrated experience in the use of statistical approaches (e.g. linear and non-linear regression)
• Demonstrated experience in use of AI/ML based approaches such as reinforcement learning, ensemble techniques, large language models etc.
• Demonstrated experience in AI/ML based frameworks such as TensorFlow, PyTorch, scikit-learn, Keras etc.
• Demonstrated experience in data visualization tools and libraries such as Matplotlib, Seaborn etc.
• Demonstrated experience in leveraging data from on-prem and/or cloud-based data pipelines such as Apache Airflow, AWS Glue etc.
• Well-versed in delivering effective communications and experience in addressing the needs of business teams
• Native English speaker, or fluent with idiomatic command of English, and demonstrably high verbal and written English skills
• Excellent interpersonal skills including the ability to work effectively with other national and cultural backgrounds
• Superior analysis and insight generation capacity
• Excellent eye for detail, critical thinking, high standards of excellence, personal organization, prioritization and time management skills, flexibility, and the ability to deliver on agreed deadlines.
• Ability to work with a considerable amount of autonomy.