Data Scientist We’re building a universal data API that lets brokers, TMSs, fintechs, and fleets connect to truck and trailer data through a single integration. Catena sits beneath the freight ecosystem, normalizing real-time telematics and execution data so platforms can automate workflows, reduce risk, and make better decisions. As a Data Scientist at Catena, you’ll focus on turning large-scale, messy logistics data into clear insights, proof points, and decision-ready outputs that power product direction, GTM motion, and customer conviction. This is not a research-only or academic role. You’ll work directly with real production data from hundreds of thousands of trucks and trailers and collaborate closely with product, engineering, and go-to-market teams to show what’s possible with Catena’s data layer. Role Summary You’ll own the analysis, exploration, and synthesis of Catena’s data to support three core objectives: - Prove value to TMSs, visibility platforms, brokers, and shippers - Enable GTM with concrete demos, sandboxes, and ROI-driven examples - Inform product strategy with real-world patterns from the network You’ll help create large-scale sandboxes, identify patterns like capacity availability, lane behavior, dwell, and utilization, and translate those into narratives customers can immediately understand. What You’ll Do Insight Generation & Analysis - Analyze large-scale telematics and execution data across fleets, lanes, and time - Identify patterns in capacity, utilization, dwell, reliability, HOS, and asset behavior - Develop metrics and summaries that reflect real-world freight performance GTM Enablement - Build and maintain large-scale sandboxes (1,000+ vehicles) using masked or synthetic data - Create compelling examples for sales, pilots, and customer conversations - Partner with GTM to turn raw data into clear ROI stories and proof points Product & Platform Feedback - Surface data-driven insights that influence roadmap priorities - Validate assumptions about customer use cases with real network data - Help define “decision-grade” metrics that customers actually trust Cross-Functional Collaboration - Work closely with product, engineering, and FDEs to understand data nuances - Support pilots and strategic accounts (e.g., TMS, visibility, broker platforms) - Translate technical findings into clear narratives for non-technical audiences Data Quality & Modeling (Lightweight) - Help define data quality checks, thresholds, and confidence measures - Assist in shaping normalized views (lane history, asset identity, availability) - Focus on interpretability and usability over black-box modeling Skills & Qualifications - Strong analytical foundation with experience in Python, SQL, and data analysis workflows - Comfort working with large, messy, real-world datasets - Ability to reason about operational systems using imperfect data - Experience turning analysis into clear business insights and narratives - Strong communication skills across technical and non-technical teams - Comfortable working in ambiguity and early-stage environments Ideal Candidate Profile - 3–6+ years in data science, analytics, or applied research roles - Experience in logistics, supply chain, marketplaces, or networked platforms is a big plus - Excited about building examples and insight, not just models - Enjoys working close to customers and real business problems - Pragmatic, curious, and impact-driven Why Join Us? - Real Impact: Your work ships to production fast with major freight platforms - Product Influence: FDE insights directly shape the roadmap - Real Scale: Hundreds of thousands of trucks, 130+ telematics providers - High Ownership: No ego, execution-driven culture - Remote-First: Flexible work with optional travel and team meetups - Momentum: Customers use us in production and many are investors Compensation: Competitive salary + meaningful equity, full benefits, 401k match Company Description Catena builds the connectivity infrastructure freight has been missing. We unify telematics, sensors, and operational data into a single API so logistics platforms can automate workflows, reduce fraud, improve safety, and build better products. We’re operators who’ve lived these problems inside carriers, brokerages, TMSs, and financial institutions. We care about accuracy, coverage, and real outcomes not hype. Catena has raised $8.25M from Shaper Capital, Floating Point, Plug and Play, Liquid 2, and leading industry angels.

About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. As a key member of our Data Science team, you'll be responsible for turning data into actionable insights, driving business decisions, and owning analytics projects from inception to completion. Day to day, your role will involve developing customized reporting and analytics tools to meet the unique needs of our clients. What you'll do: - Write production code in Python. - Design, launch, and analyze experiments to optimize ad campaigns. - Create reporting and analytics tools for the Data Science Team's customers. - Translate insights from reporting tools into tvScientific's Data Science Product. What we're looking for: - Ability to write and review production-level code in Python. - Strong statistics and ML fundamentals. - Desire to work in a fast-growing environment—comfortable with ambiguity, ownership, scaling new products, and an experimental, iterative development process. - Experience defining and measuring the utility of new reporting and analytics tools. - Ability to quickly translate between DS Analytics & DS Product team. - Strong track record of providing high-quality service to the DS team’s customers/stakeholders. - Adtech or CTV experience. - Teaching experience is a plus. - Big data experience with Scala, Apache Spark, Apache Beam, and AWS Athena is a plus. In-Office Requirement Statement: - We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role. Relocation Statement: - This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. #LI-SM4 #LI-REMOTE At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $139,764—$287,749 USD

• Conduct comprehensive data evaluations for prospective partners, demonstrating SentiLink's product value through clear data science metrics. • Analyze performance data from current partners to ensure optimal product use and provide actionable recommendations. • Collaborate with cross-functional teams, including Product, Data Science, and Engineering, to enhance product performance and address partner-specific needs. • Deliver ad hoc analyses and reports that provide deep insights into fraud trends, consumer behavior, and partner-specific challenges. • Communicate complex data findings effectively through visualizations, reports, and presentations tailored to both technical and non-technical stakeholders

We are seeking a highly motivated Data Scientist to join our remote analytics team. In this role, you will leverage advanced statistical analysis, machine learning, and data modeling techniques to generate insights that drive strategic decision-making across the organization. The ideal candidate has a strong analytical mindset, experience working with large datasets, and the ability to translate complex data into clear business recommendations. This position offers the opportunity to work with cross-functional teams including engineering, product, finance, and operations to build scalable data solutions and predictive models. Key Responsibilities Data Analysis & Modeling * Analyze large, complex datasets to identify trends, patterns, and actionable insights. * Develop and deploy predictive models, machine learning algorithms, and statistical analyses. * Perform exploratory data analysis (EDA) to support business problem-solving. * Build and maintain data pipelines to support analytics and modeling efforts. Machine Learning & Predictive Analytics * Design and implement machine learning models for forecasting, classification, clustering, and optimization. * Evaluate model performance and refine algorithms to improve accuracy and scalability. * Conduct A/B testing and experimental analysis to support product and operational improvements. Data Visualization & Reporting * Develop dashboards, reports, and visualizations using tools such as Power BI, Tableau, or Python libraries. * Present analytical findings and insights to stakeholders in clear and actionable formats. * Translate complex data concepts into understandable business recommendations. Collaboration & Strategy * Work closely with engineering and product teams to integrate data science solutions into production systems. * Support strategic initiatives through data-driven insights and forecasting. * Ensure data accuracy, governance, and compliance with internal standards. Required Qualifications * Bachelors or Masters degree in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field. * 3+ years of professional experience in data science, analytics, or machine learning roles. * Strong programming skills in Python or R. * Experience with SQL and working with large datasets. * Solid understanding of statistical modeling, machine learning techniques, and predictive analytics. * Experience with data visualization tools such as **Tableau, Power BI, or similar platforms. * Strong problem-solving, analytical, and communication skills. Preferred Qualifications * Experience with cloud platforms (AWS, Azure, or Google Cloud). * Familiarity with big data tools such as Spark, Hadoop, or Databricks. * Knowledge of deep learning frameworks (TensorFlow, PyTorch). * Experience working in remote or distributed teams. Compensation & Benefits * Flexible remote work schedule. * Performance-based incentives and professional development opportunities. * Access to advanced data science tools and resources. * Collaborative remote work environment with opportunities for career growth. Eligibility Requirements * Must reside in the United States. * Must have valid U.S. work authorization (U.S. citizen, permanent resident, or authorized work permit holder). * Ability to work remotely with a reliable internet connection and secure home workspace.