Job Description
Overview
You will be part of a collaborative interdisciplinary team around data, where you will be responsible of building deployable statistical/machine learning models, beginning from the discovery phase through to implementation. You’ll collaborate closely with process owners, product managers, and end-users to ensure your developments are aligned with business priorities and drive measurable outcomes.
You will be an internal ambassador of the team’s culture around data and analytics fostering a culture of innovation, analytics, and collaboration fostering a culture of innovation, analytics, collaboration, and being a data driven leader . You will provide stewardship to colleagues in the areas that you are a specialist or you are specializing contributing to the team’s growth and success in data and analytics.
Responsibilities
- Contributing member in a digital project acting as tech lead for the project.
- Act as a subject matter expert in one other digital project.
- Support lead contributor in innovation activities
- Partner with product managers in taking DS requirements and assessing DS components in roadmaps.
- Partner with data engineers to ensure data access for discovery and proper data is prepared for model consumption.
- Partner with ML engineers to industrialize solutions.
- 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.
- Support large-scale experimentation and build data-driven models.
- Set KPIs and metrics to evaluate analytics solution given a particular use case.
- Refine 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
- 4+ years’ experience building solutions in the commercial or in the supply chain space.
- 4+ years working in a team to deliver production level analytic solutions. Fluent in git (version control). Understanding of Jenkins, Docker are a plus.
- 4+ years’ experience in ETL and/or data wrangling techniques. Fluent in SQL syntaxis.
- 2+ years’ experience in Statistical/ML techniques to solve supervised (regression, classification) and unsupervised problems. Experiences with Deep Learning are a plus.
- 2+ years’ experience in developing business problem related statistical/ML modeling with industry tools with primary focus on Python or Scala development.
- 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 analytics ‘product’ creation. Fluent in Jira, Confluence.
- Experience with Azure cloud services is a must.
- Experience in Reinforcement Learning is a plus.
- Experience in Simulation and Optimization problems in any space is a plus.
- Experience with Bayesian methods is a plus.
- Experience with Causal inference is a plus.
- Experience with NLP 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