This role involves leading the development of analytics tools and models, and creating informed recommendations to attract and retain top-performing drivers, identify and reduce operational risk, and improve fleet health and efficiency. The Data Analytics Lead will work cross-functionally to turn complex data into actionable insights and strategic recommendations, analyzing customer feedback, interaction data, payments, maintenance records, telematics, product usage, and fleet operations.
Transform data into powerful stories that drive real-world results. Dig deep into complex datasets, uncover meaningful trends, and deliver strategic insights that directly shape business outcomes. As part of our dynamic Analytics Team, collaborate closely with clients to turn complex data into meaningful insights. Contribute to internal knowledge-sharing and support team growth through peer collaboration and training.
As a Senior Microsoft Fabric Data Engineer, you will be responsible for designing, implementing, and managing advanced data engineering solutions using Microsoft Fabric, working closely with an Implementation Partner to ensure seamless execution and optimization of data platforms for an End client. You will develop, implement, and manage data engineering solutions leveraging Microsoft Fabric and collaborate with TCS teams to ensure project objectives align with organizational needs.
We’re looking for an experienced, hands-on Data Scientist to embed into and support analytics within RevOps and Finance teams. You will ensure data quality & integrity, develop data models, build intuitive dashboards for revenue insights, support ad hoc analysis and strategic questions, and document processes & methodologies.
We’re looking for a passionate Senior Analytics Engineer to help us bring our data platform to the next level. This includes modelling our data for final consumption and leading the design of a new semantic layer. Collaborate with engineers, product teams and analysts to develop data products that are precise and insightful. Find creative ways to integrate AI into the Data lifecycle. Own the data product lifecycle, including designing tracking plans, developing data models, ELT pipelines, and self-serve data products. Be the data steward, ensuring data quality and consistent metrics.
Work on end-to-end data projects with the Ad Network squads to improve performance and drive targeting and revenue improvements. You'll gather needs from stakeholders, share progress and provide actionable recommendations. Build data collection and transformation pipelines, and actionable dashboards. Analyze large, complex data sets with billions of events.
Lead a team of data professionals dedicated to supporting Revenue, Marketing, and Finance teams. You will oversee the business intelligence system, data analysis, and data strategy, playing a critical role in driving data-informed decision-making and fostering a culture of analytics excellence. Balance strategic vision with operational execution to empower stakeholders across the organization to achieve their goals through actionable insights!
To train Gen AI models you will craft and answer questions related to computer science in order to help train AI models. You will also evaluate and rank code generated by AI models.
The intern will contribute to building scalable data solutions that support CALSTART's mission while gaining hands-on experience in cloud-based data engineering and data science. This project will focus on creating a data lake environment, developing automated data pipelines, and designing powerful visualizations to gain insights into clean vehicle adoption, infrastructure planning, and sustainability efforts.
Reporting to the Senior Manager of Development and Operations, you will be an expert in designing and developing end-to-end data solutions from source data ingestion, ETL process, visualization, and to business insights delivery. You will identify automation opportunities in existing data pipelines and propose design of the automation process. You will collaborate with Engineering teams to discover and use data being introduced into the environment.