Data Scientist, Model Development Lead

This role leads the design and execution of data analysis and machine learning projects. On small to medium-sized projects, the data scientist is expected to act as a project leader or sub-leader, guiding work from organizing client issues and developing hypotheses through analysis and reporting.

Responsibilities include project progress management, leading small teams, client discussions and support for proposals, hypothesis development, analysis planning, data collection, data processing and preprocessing. The role also covers modeling using machine learning, statistical modeling and mathematical optimization, visualization and reporting of analysis results for internal and external audiences, technical support for turning proof-of-concept results into systems, and internal knowledge sharing and standardization activities.

The role supports projects intended to address both individual client needs and broader industry-wide optimization. It may involve project design, requirements definition and proposal activities, as well as collaboration with large companies on longer-term value creation initiatives.

The development environment includes SQL and Python, with R used depending on the project. Cloud environments include GCP, AWS and Azure. Source code is managed with GitHub, projects are managed with Jira, and information sharing uses Slack and Confluence.

Applicants should have practical experience as a data scientist or a degree in a related field, specialist knowledge of machine learning, deep learning or statistical modeling, and development experience using Python, R or SQL. The posting also seeks the ability to explain specialist technology accurately and clearly, and an interest in organizational operations and talent development.

Possible career paths include analysis specialist, project leader and business planning support. Depending on the individual career plan, management and expert tracks may be selected. The role also provides opportunities to develop others, support client-company growth through applied projects, experience varied applications of analysis, and advance business use of data analysis and AI technology.