דרושים » תוכנה » Analytics Engineer

We are seeking an experienced sharp and dynamic analytical mind to join our Product Analytics team as a Strategic product analyst. This position is ideally suited for those who are naturally passionate about learning, gaining knowledge, and analyzing anything they do and see with experience in utilizing data to make a significant impact.
The role requires a combination of analytical, technical, problem-solving, communication, and project management skills, and it involves working closely with various stakeholders and customers - including Product Managers, Customer Success Managers, Operations teams, Data Engineers, UI/UX Designers, SW developers, and AI experts at all levels.
Responsibilities:
As a Strategic product analyst at Aidocs Analytics group, you will play a critical role in expanding our data-driven vision and building analytics capabilities that create value for both our customers and internal teams. Your work will include:
Building scalable customer-facing analytics and data-sharing products, transforming complex data and customer needs into reliable, intuitive, and standardized solutions.
Partnering with Customer Success and Product teams to understand how customers use our products, identify opportunities to improve adoption and demonstrate value, and translate site needs into scalable analytical solutions.
Leading strategic analyses across products, workflows, and clinical domains, connecting data from multiple parts of Aidocs ecosystem to uncover insights and support business and product decisions.
Designing product KPIs and measurement frameworks, monitoring trends, and working with key stakeholders to translate findings into actionable insights.
Conducting decision-support analyses for Product, Customer Success, development, and operational initiatives.
Designing and improving scalable data models and analytics infrastructure that support customer-facing products, internal analytics, and repeatable analytical capabilities.
Continuously expanding our analytics knowledge base, improving data quality and reliability, and documenting learnings to strengthen the teams collective expertise.

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.

we are looking for a Data Analyst.
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 Autofleet 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.

We are seeking a talented and motivated Data Scientist for a temporary position to support our growing data, analytics, and AI automation needs. This role focuses on turning large volumes of data into models, insights, and intelligent automation - combining classic data science (statistical analysis, feature engineering, machine learning) with the emerging Agentic AI stack (LLMs, MCP, agent orchestration). You will work closely with data engineers and internal teams to prototype and productionise models, build LLM-powered agents and workflows, and support the integration of AI capabilities across the organization.

The ideal candidate is passionate about data and AI, comfortable navigating complex systems, and excited by the opportunity to operationalize AI within a modern enterprise environment. We value curiosity as much as experience: we are looking for someone eager to show what they know, and equally eager to keep learning in a field that moves fast.


Responsibilities
Explore, analyze, and model large volumes of structured and unstructured data in Python, from exploratory analysis and feature engineering through to model validation and communication of results.
Design, train, evaluate, and deploy machine learning models, and monitor their performance, accuracy, and drift in production.
Build and orchestrate Agentic AI solutions - LLM-based agents, RAG pipelines, prompt design, and evaluation frameworks - to automate data quality checks, investigation, and reporting workflows.
Integrate models and agents with internal systems and data sources using MCP servers and clients, and workflow automation platforms such as n8n.
Write efficient and maintainable SQL queries to support analysis, reporting, and data exploration needs.
Collaborate with data engineers to productionise models and agents: reliable data flows, logging, alerting, and performance tuning.
Participate in the development of internal tools and dashboards that make data and AI capabilities accessible across the organization.
Share findings with the team and help evaluate emerging AI tooling as the ecosystem evolves.

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 which will help answer client's business. questions by using raw data sets and algorithms.
Partner with Engineering teams to establish an infrastructure to scale solutions.
Partner with Advisory Services team of Consultants to answer strategic business questions and deliver custom data products seamlessly

Were looking for a Data & Analytics Team Lead to manage and grow our data team and own the data layer behind our AI. Youll lead a team of data analysts responsible for neural-network model analysis, model performance tracking, customer-facing and internal BI. Youll act as both the people manager and the technical lead for the team, setting technical direction while staying hands-on.
Youll thrive in this role if youre passionate about turning data into better AI products, enjoy solving complex analytical problems, and like working at the intersection of Data, Analytics, and Artificial Intelligence.
Responsibilities:
Lead the data strategy supporting AI model development, evaluation, and continuous improvement
Define KPIs and monitoring frameworks for AI model performance.
Analyze NN model outputs, build and maintain model-tracking and performance-evaluation workflows
Drive close calibration with the Algo, Product, and Data Engineering teams to align data definitions, pipelines, and metrics
Stay hands-on with SQL, Python, BI tooling, and the modern data stack
Build and own agentic data workflows - designing the context, tooling, and data access that let AI agents reliably query, analyze, and act on company data

We're looking for a Senior Data Product Manager to lead our analytics and insights platform. At the core of the role is owning the story data tells: speaking the language of C-suite and senior executives, and translating complex data into clear insight and business impact, helping health system leaders gain unique insights on their business and their patients. You're a true data enthusiast with strong business sense and an analytical mindset: you proactively identify opportunities, build conviction, and align stakeholders to drive execution. And you care about the customers behind the data. You sit with users, understand how they consume data and where they get stuck, and turn that into product direction.

You'll join our Platform group and lead the strategy, roadmap, and execution of Hyro's analytics and insights platform. This core system turns data into actionable insight for our customers, powering customer-facing reports, our insight engine, and the underlying data infrastructure.

This is a senior IC role with end-to-end ownership over a critical, highly strategic product area. You'll work at the intersection of data, business, and engineering, translating a deep understanding of customer needs, business goals, and the technical aspects of the platform into an analytics strategy that drives growth.

Responsibilities
Define and drive the strategy, roadmap, and prioritization for our analytics product.
Own the end-to-end experience of our analytics product - including customer-facing reports and our insight engine, the primary way customers and internal stakeholders consume data-driven insights.
Partner closely with engineering and data teams to build and evolve the data infrastructure that powers reporting and insight generation.
Translate customer, business, and market insights into clear product direction and high-impact initiatives.
Define success metrics, track performance, and use data to inform decisions and communicate impact.
Partner with and present to senior leadership and C-level stakeholders, translating data into business strategy and growth opportunities.

We are looking for a sharp and driven Data Solutions Analyst to join a newly formed team and help build the analytical foundations behind some of our strategic growth initiatives from the ground up. This is a unique opportunity to influence how new businesses operate and scale across Amazon, D2C, Paid Media, and emerging growth channels. You will have ownership over both the measurement frameworks and the solutions that drive business growth.

Working at the intersection of Data, Marketing, Product, and Business, you will identify opportunities, define success metrics, uncover insights, and build the solutions needed to turn those insights into action. This role combines analytical ownership with hands-on solution development, leveraging data, automation, AI, and modern tooling to solve business challenges end-to-end. Success in this role is measured not only by the quality of your analysis, but by your ability to translate business challenges into scalable solutions that drive measurable impact.

Roles and Responsibilities:
Build analytical infrastructure, measurement frameworks, and decision-support capabilities from the ground up for new and rapidly growing business units.
Evaluate performance across Amazon, D2C, Paid Search, Paid Social, and emerging channels, identifying growth opportunities, business risks, and areas for optimization.
Translate business challenges into scalable solutions by combining AI powered automation, agents, workflows, and building tools that drive business impact.
Design, build, and maintain dashboards, monitoring systems, analytical products, and self-service tools that enable teams to make faster and better decisions.
Own the Semantic Layer: Maintain and scale our unified BigQuery Semantic Layer, ensuring a single source of truth for business and analytics metrics.
Partner closely with Marketing, Product, and Business stakeholders to understand business needs and drive end to end solutions from idea to implementation.

we are looking for a Data Analyst
Responsibilities

Own and define key product, business, and customer KPIs across the company
Analyze usage, funnels, monetization, and customer behavior to identify growth opportunities and friction points
Build and maintain dashboards and reports that give teams clear, reliable visibility into performance
Partner with Product and Business to evaluate new features, initiatives, and experiments, and measure their impact
Drive customer value by delivering external-facing data solutions, actionable insights, and industry benchmarks to empower data-informed decision-making.
Work closely with engineering and data stakeholders to improve data quality, structure, and accessibility
Help foster a data-driven culture by making insights understandable and actionable for non-technical stakeholders

Required Data Scientist, Product Analytics
As a Data Scientist, you will shape the future of people-facing and business-facing products we build across our entire family of applications. By applying your technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a varied set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance and others. You will use data and analysis to identify and solve product development's biggest challenges. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining us, you will become part of a analytics community dedicated to skill development and career growth in analytics and beyond.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and us. You will help your partner teams prioritize what to build, set goals, and understand their product's ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a varied toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches to test them.
Communication and influence: You won't simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.
Data Scientist, Product Analytics Responsibilities
Defining new opportunities for product impact Influencing product and sales to solve the most impactful market problems
Apply your expertise in quantitative analysis and the presentation of data to go beyond the numbers and understand how our users interact with our growth products
Work as a key member of the product team to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches in partnership with Product, Engineering, and cross-functional teams
Set KPIs and goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics
Exploratory analysis to discover new opportunities: understanding ecosystems, user behaviors, and long-term trends Identifying levers to help move key metrics.