Machine Learning Scientist

Details

Responsibilities

• Translate specific business problems into ML/AI challenges and develop a targeted research plan to identify the best approach within the constraints of the production environment.
• Develop the strategy for machine intelligence on a specific product by designing innovative ML/AI models, algorithms, and approaches that deliver both short-term commercial impact and longer-term differentiated business value and customer experiences.
• Define and build proof-of-concepts to test new ideas and demonstrate their potential value to relevant stakeholders.
• Drive the end-to-end execution of the ML/AI development process on specific products, from understanding product requirements, data discovery, model development and evaluation, to implementation of a full production pipeline for both batch- and stream-based deployment.
• Develop production-grade ML code for models, features, and pipelines, accounting for scalability, latency, realtime requirements, monitoring and retraining.
• Build readable and reusable code, using the right technologies and coding methodologies applying knowledge of business area tools and product needs.
• Maintain a highly cross-disciplinary perspective, solving issues by applying approaches and methods from across a variety of ML/AI disciplines and related fields.
• Support others through evidence and clear communication, explaining advanced technical concepts in simpler terms.
• Continuously evolve your craft by keeping up to date with the latest developments in ML/AI and related technologies and upskilling on these, as needed.
• Responsible for data management related Data Governance processes as defined in the Data Governance Framework (e.g. monitoring of data quality, management of data lineage, and maintenance of logical data model).

Requirements

• Subject matter expertise in one or more areas of ML/AI (e.g. Recommender Systems, Deep Learning, Forecasting, Natural Language Processing, Computer Vision)
• Ability to define a machine intelligence strategy on a specific product by identifying short-term development steps that create immediate business value and build upon each other to create longer-term differentiation
• Ability to design an applied research plan from scratch as evidenced by peer-review publication or similar track record
• Ability to execute end-to-end research and development plans and generating impact through large-scale machine learning model development.
• Relevant work or academic experience (MSc + 3 years of working experience, or PhD), involved in the development and application of Machine Learning.
• Strong working knowledge of big data technologies
• Strong working knowledge of Python, Hadoop, SQL, R, Spark or similar technologies.
• Excellent English communication skills, both written and verbal.