Data Scientist

Responsibilities

• Contribute member in a digital project.
• Present your findings in a business friendly manner to our stakeholders.
• Build machine learning models with minimal oversight.
• Act as a subject matter expert in our digital project to other teams.
• Partner with product managers in proving feedback on story points and tickets.
• Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
• Contribute with work activities that involve Business teams, other IT services and as required.
• Drive the use of the Platform toolset and to also focus on 'the art of the possible' demonstrations to the business as needed.
• Communicate with business stakeholders in the process of service design, training and knowledge transfer.
• Drive large-scale experimentation and build data-driven models.
• Set KPIs and metrics to evaluate analytics solution given a particular use case.
• Refined requirements into modelling problems.
• Influence product teams through data-based recommendations.
• Research in state-of-the-art methodologies.
• Create documentation for learnings and knowledge transfer.
• Support in creation reusable packages or libraries.

Qualifications

• 3+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems.
• 3+ years’ experience in developing business problem related statistical/ML modeling with primary focus on Python development.
• 2+ years’ experience working with modern cloud platforms to power ML solutions.
• 2+ years working in a product focused team to deliver production level analytic solutions.
• Business storytelling and communicating data insights in business consumable format.
• Fluent in one Visualization tool.
• Strong communications and organizational skills with the ability to deal with ambiguity while juggling multiple priorities.
• Experience with Agile methodology for team work and product creation.
• Experience in Reinforcement Learning is a must.
• Experience with Pyspark is a must.
• Experience with SQL is a must.
• Familiarity with git, understanding of Jenkins or Docker a plus.
• Experience with NLP is a plus.
• Experience with LLM is a plus.
• Experience with working with FAIR data is a plus.
• Experience with Responsible AI is a plus.
• Experience with distributed machine learning is a plus.