דרושים » תוכנה » Analytics Engineer

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.

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'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.

A Product Analyst at Torq plays a key role in helping Product teams understand whats happening, why its happening, and what to do next. By proactively identifying trends, asking the right questions, and connecting insights across product and user data, youll help shape product decisions and identify opportunities for improvement.

What You Will Do:
Proactively identify trends, opportunities, and product questions, turning data into actionable insights and recommendations.
Deep dive into user behavior, product performance, adoption, funnels, and usage to understand not only what is happening, but why.
Partner with Product to define meaningful KPIs, monitor performance, and use A/B testing and other analytical methods to identify opportunities for improvement.
Work closely with Product, R&D, and other stakeholders to translate insights into product priorities and decisions.
Build dashboards, reports, and analytical frameworks that help teams understand product performance and make better decisions.
Ensure accuracy and attention to detail, building trust in the data and insights used across the organization.

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 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.

We are looking for a Product Analyst Team Lead to lead and develop our Product Analytics team. In this role, youll set the teams direction and priorities, develop and grow the team, and work closely with Product and senior leadership to ensure analytics drives meaningful product and business decisions.
What You Will Do:
Manage, mentor, and grow a team of Product Analysts, building a strong and high-performing analytics function.
Define the teams direction, prioritize high-impact initiatives, and proactively identify future product and business needs.
Lead the team in defining KPIs and turning complex product and business questions into actionable insights and recommendations.
Partner closely with Product, R&D, Data, Field, Sales, and senior leadership to influence product and business decisions.
Remain close to the data and lead key analyses when needed, while focusing primarily on leading the team and its impact.

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

Were looking for a Data Analyst to join our growing data team and help make analytics a core part of how we build. Youll work on the product-usage side of an AI product that thousands of developers rely on - understanding how teams adopt AI code review, which features drive value, and where we can make the experience better. Its a product-focused role at heart, reaching into business, operational, and cost metrics too, with room to shape how we work as the team grows.

Be the go-to analyst for the product team - drive product analytics day to day: how developers use our AI features, plus retention and conversion funnels.
Turn raw product and usage data into clear, consistent metrics the team can trust.
Build and maintain the modeled data layer, so metrics live in one place and analysis is repeatable rather than rebuilt each time.
Build and maintain dashboards so teams can self-serve answers.
Run deep-dive analysis to surface opportunities and support product decisions and experimentation.
Extend into business and operational KPIs - conversion, churn, segmentation, customer value - and cost / unit-economics.
Take analyses from problem definition through to clear recommendations, not just reports.

We're looking for Product Data Analyst to own the numbers behind Ace and play a central role in shaping product decisions. Youll work closely with Product, Engineering, Growth, and company leadership to understand how people use Ace
Youll own the analytical process end to end: identifying the right questions, defining metrics, designing experiments, working directly with product data, interpreting results, and translating findings into clear product decisions.
We move fast, experiment constantly, and expect analysts to be hands-on, curious, technically strong, and comfortable challenging assumptions.
What You'll Do:
Own the consumer funnel end to end. Analyze acquisition, install, onboarding, activation, engagement, retention, and monetization across desktop and mobile. Identify where users drop, understand why, quantify the opportunity, and turn insights into concrete product opportunities.
Run the experimentation engine. Own experiments end to end - identify whats worth testing, define the right metrics and methodology, analyze the results, and translate learnings into clear product decisions.
Go deep into the data. Work directly with large-scale behavioral data to investigate questions, uncover patterns, diagnose problems, and find opportunities that arent obvious from a dashboard.
Shape how we measure the product. Define the metrics that matter, make sure were measuring new features correctly, and create a trusted analytical foundation for understanding product performance.
Be a strategic product partner. Work closely with Product and leadership to frame important questions, challenge assumptions, and bring a strong data-driven perspective to product strategy and prioritization.
Use AI to work differently. Use modern AI tools as part of your daily workflow to explore faster, investigate deeper, automate repetitive work, and build lightweight solutions when needed.
Make the organization faster with data. Build frameworks and self-service capabilities that help teams answer common questions independently, so your time stays focused on the highest-impact problems.