We're looking for an experienced Data Analyst to join our growing Data team and help shape one of the core functions at our company.
This isn't a traditional BI or Product Analytics role. You'll work across engineering, data science, product, research, and customer-facing teams to understand complex data from enterprise environments, transform it into a consistent data model, and generate insights that directly power our product and customer experience.
You'll wear multiple hats-from researching new data sources and designing scalable data models to supporting customer onboarding, surfacing meaningful insights, and helping define how our data platform evolves as the company grows. This also means getting hands-on in the codebase: you'll regularly modify logic in production system components, not just analyze data from the outside.
If you're someone who enjoys turning messy data into clear decisions, thrives in ambiguous environments, and wants to build the foundations of a data function from the ground up, we'd love to meet you.
What You'll Do
Research and evaluate new customer data sources, APIs, and integrations, understanding what data is available, how reliable it is, and how it can create value.
Analyze large, complex datasets to identify patterns, anomalies, and actionable insights that improve our product and customer outcomes.
Design and evolve our company's data models, creating a unified language across data coming from multiple integrations and systems.
Partner closely with Engineering and Data Science teams to define schemas, data structures, and scalable modeling approaches.
Build and modify logic in system components as part of regular delivery, not just spec it for someone else to build.
Support customer onboarding by validating incoming data, identifying issues, and ensuring customers receive meaningful insights from day one.
Deliver customer-facing analyses, reports, and recommendations while working against real customer deadlines.
Help define the foundations of our company's data function by evaluating tools, methodologies, and best practices that will scale with the company.
Work closely with Product to ensure product decisions are informed by data and grounded in real customer behavior.
Collaborate on AI-powered capabilities by helping define the data, signals, and requirements that enable intelligent product features and autonomous workflows.

Required Data Analyst
Description
We're transforming the way fleets operate by leveraging data, automation, and AI to power smarter mobility. As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform
What youll do:
Own the product analytics domain for key products and strategic initiatives, with a focus on user behavior and product engagement.
Design, build, and own our product analytics infrastructure (event tracking, taxonomy, instrumentation) from the ground up, primarily using Mixpanel.
Define and maintain a clean, scalable event-tracking taxonomy in partnership with Engineering and Product.
Analyze large-scale product and behavioral datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using Mixpanel and other modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs and metrics (activation, retention, funnels, engagement), measure success, and support product decision-making.
Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
Build internal tools and processes that improve data accessibility and operational efficiency.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

Were looking for a Analytics Engineer to own the data and analytics foundation that helps Product, Growth, Customer Success, R&D, and leadership make better decisions.
Youll own the path from raw data to actionable insight - building reliable models, defining key metrics, analyzing product and business performance, and communicating what the data actually tells us.
What youll do:
Analyze product and business performance: Track core KPIs, investigate trends and anomalies, and analyze product usage, feature adoption, customer behavior, funnels, and retention to identify opportunities for improvement.
Turn data into actionable insights: Translate analytical findings into clear recommendations that help Product, Growth, Customer Success, and leadership make better decisions.
Evaluate product initiatives: Measure the impact of new features, product changes, and experiments using appropriate analytical and statistical methods.
Own analytical data models: Develop and maintain reliable, well-structured data models that support consistent metrics, self-service analytics, and trusted business reporting.
Improve the analytics foundation: Contribute to the evolution of our analytics infrastructure, data quality, and tracking in collaboration with Engineering and other stakeholders.
Build and communicate insights: Develop dashboards and targeted analyses, and present findings clearly to technical and non-technical stakeholders, connecting results to business impact.

Were looking for a sharp and driven Product Data Scientist to join our fast - paced Data Labs team.
As part of a high-performing group of analysts, youll handle complex, custom requests from some of the biggest names in the market, turning raw data into strategic, ad hoc insights.
The work is intense and constantly evolving - it requires strong analytical skills and the ability to work independently under pressure.
Youll need to be curious, adaptable, and willing to dive deep to find answers where others might stop. If you thrive in a demanding environment and are excited by the opportunity to make a real impact, we want you on our team.
What does the day-to-day of a Product Data Science Customer Facing (Data Labs) look like:
Building custom-made reports end to end - from meeting with the client and understanding their needs, to writing the code and setting up the report for ongoing delivery.
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will help answer clients business questions by using our raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with the Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly.

In this role, you will operate as a company-level expert in product analytics, partnering with Product, Engineering, and cross-functional leadership to translate complex, large-scale behavioral data into actionable insights that shape the experiences of billions of people worldwide. You will lead the design of rigorous analytical frameworks, advance forecasting and predictive modeling capabilities, and influence the highest-priority product investments through data-driven storytelling and strategic recommendations.
Data Scientist, Product Analytics Responsibilities
Lead the design and execution of complex analytical projects across product areas, applying advanced statistical methods, causal inference, and experimentation to evaluate product impact at scale
Develop and maintain sophisticated predictive models and forecasting frameworks to inform product roadmaps, goal setting, and resource prioritization
Define and evolve success metrics and measurement strategies for product initiatives, ensuring goals accurately reflect user and business value
Identify and size high-impact product opportunities by synthesizing behavioral data, qualitative signals, and business context across multiple data sources
Partner with Product and Engineering teams to design and analyze large-scale A/B tests and feature rollouts, translating results into clear recommendations for product direction
Build scalable, self-service data pipelines and visualization interfaces that enable cross-functional teams to explore and act on product performance data independently
Communicate complex analytical findings to diverse audiences including product leadership and executives through concise, compelling data narratives and presentations
Contribute to functional data science strategy by proactively identifying methodological gaps, championing analytical best practices, and setting goals across teams
Mentor other data scientists on analytical design, hypothesis formulation, and quantitative modeling, elevating the overall quality and rigor of the team's work
Collaborate with Data Engineering and Research partners to improve data infrastructure, eliminate bias in data collection, and ensure analytical outputs accurately represent the populations of interest

This is a high-ownership role combining strong business judgment with deep technical capabilities. You will contribute to strategic initiatives, work closely with Product Managers, engineers, and senior leadership, and help shape how decisions are made across the company.
You will work primarily with dbt, BigQuery, Looker, and GitHub, using AI-enabled tools such as Cursor, MCP integrations, n8n, and OpenClaw to accelerate and automate your work.
For us, AI-native means more than generating SQL in a chatbot. It means giving agents the right context and tools, validating their output, and turning repeatable processes into reusable workflows.
Product data is consumed throughout Connecteam. Success in this role therefore requires excellent communication, proactive ownership, and the ability to translate complex analysis into practical business recommendations.

Key Responsibilities
Partner with Product Managers and engineers to define events, funnels, activation criteria, adoption metrics, and post-launch measurement.
Analyze high-impact questions involving signup conversion, first-day behavior, feature adoption, retention, and release performance.
Contribute to strategic projects and provide leadership with trusted insights and actionable recommendations.
Define and validate analytics events, then integrate them into our usage, 360, and feature-usage models.
Extend and validate dbt models, owning changes through pull request and CI.
Build and maintain focused Looker dashboards that support product decisions.
Investigate anomalies, usage drops, tracking failures, spam, and inconsistent metrics.
Turn repeatable analyses and operational processes into agent skills, rules, and automated workflows.

We are looking for a highly analytical AI Product Analyst to join our core Product Analytics tech team. Operating at the intersection of data, Product and Tech, you will be the bridge between user behavior and model performance. You will partner with Product and Tech leadership to define KPIs, build the semantic layer for Product Agents, and iterate on AI outputs. Your insights will directly impact our strategy, drive feature adoption, shape our data infrastructure, and deliver measurable business impact.
Job responsibilities
Empower Strategic Decisions: Translate complex usage data into executive-ready dashboards and actionable recommendations that align cross-functional stakeholders.
Enable AI Data Infrastructure: Build and maintain the semantic layer for Product Agents to unlock intelligent, self-serve data discovery across the organization.
Drive Product Growth: Analyze the user journey to proactively identify adoption gaps and friction points, accelerating feature activation, retention, and growth.
Optimize AI & Feature Impact: Measure roadmap launches and iterate on prompt engineering and model evaluation to continuously elevate AI performance and user experience.
Standardize Metrics & Tracking: Partner with Product leadership to define core KPIs, unify metric definitions, and establish robust event tracking.
Accelerate Delivery Velocity: Leverage AI-assisted development tools (e.g., Cursor, Claude Code) to streamline technical workflows and increase analytical output speed.

We are looking for a highly analytical, deeply technical, and proactive Senior Salesforce and Business Applications Analyst to join our team. In this role, you will champion an AI-first approach, leveraging AI across every aspect of your work to optimize efficiency and drive innovation.

You will bridge the gap between business needs and technical execution, taking full ownership of complex systems and driving end-to-end processes. Your focus will be on supporting, enhancing, and automating our operations across various business domains, including Sales, Service, and Marketing.

This hands-on role encompasses managing daily system maintenance, configuring systems, integrating AI-driven workflows, and overseeing projects from inception to completion.

Key Responsibilities:

End-to-End Project Management: Manage complex, cross-functional projects from initial ideation, through requirements gathering, to successful deployment and optimization.
Drive Innovation & Initiative: Act as a proactive change-agent. Identify business gaps, propose innovative solutions, and passionately push new initiatives forward to improve efficiency and performance.
System Ownership: Take full accountability and end-to-end ownership of the systems health, functionality, and alignment with business goals.
Mentorship & Leadership: Guide, mentor, and upskill junior team members, fostering a culture of continuous learning and professional excellence within the team.

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.

This role is diverse, encompassing AI/ML, data analysis, and backend engineering.

You will play a crucial role within a mission-critical team responsible for managing the heart and brain of Sunbits primary products. This involves working on core systems, such as POS underwriting models, models for merchant operations, Fraud investigator AI agents and more.

You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.

Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.

Key Responsibilities
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / fraud / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g. providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Analyze 15+ different data sources in order to train models and agents to catch fraudulent patterns.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

We are looking for a Data Insights & Analytics Manager who will develop a deep understanding of data generated global installed base of connected medical devices, combine it with enterprise data, and translate it into insights and tools that create value for our customers and the business.
The role goes beyond reporting and dashboard creation.
We are looking for someone who is naturally curious, proactively explores data, identifies patterns and opportunities, and drives the organization to act on what the data reveals. Importantly, the role is expected to uncover broader customer, commercial, and business insights by connecting IoT data with enterprise and other relevant data sources - not only insights derived from device data itself.