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We are looking for a Data Science / Machine Learning Engineer Tech Lead to join the data science group. Youll have the opportunity to make a significant impact by creating products that are used by millions of users around the world.
Our Data Science group is responsible for developing and implementing data-driven models, conducting research to evaluate new data science methodologies, and analyzing large datasets to extract actionable insights.
The individual will collaborate with cross-functional teams to ensure actual impact on our users and business outcomes.
Responsibilities:
Machine Learning: Design, Research, analyze, develop, and implement predictive models, from inception to production, in addition to MLOps infra for various of machine learning techniques to address complex business problems.
Code review to peers, maintain code quality, unit testing, E2E testing, ML models monitoring, maintainability and scalability
Collaboration: Work closely with cross-functional teams including Devops, Back End, and Mobile teams to define project goals and deliver data-science projects into production.
Stay updated with the latest research and advancements in AI.
Reporting: Create clear, concise, and actionable reports to communicate insights to stakeholders.

Required Data Operations Team Leader
As the Team Leader for Data Operations, you will manage a team responsible for ensuring the accuracy and quality of our mobility data. You will play a crucial role in maintaining our service by overseeing data updates, managing relationships with key partners, and engaging our user community. This is a hands-on leadership position where you will drive the team's success while also contributing directly to our mission of simplifying mobility.
Responsibilities:
Team Leadership & Management: Lead, mentor, and manage a team of data operations specialists, ensuring high performance and continuous development.
Data Quality Ownership: Oversee the process of identifying, correcting, and improving public transit and mobility data to ensure our app provides accurate and up-to-date information.
Stakeholder Management: Build and maintain strong relationships with transit authorities and partners to understand their needs and ensure their success.
Community Engagement: Work closely with our local community of users to perfect data and increase engagement through various initiatives.
Process Improvement: Identify opportunities to improve data collection, analysis, and quality assurance processes.
Cross-Functional Collaboration: Support regional and cross-departmental initiatives, working with other teams to deliver on business goals.