דרושים » תוכנה » A global technology company is looking for an experienced data Scientist - Product Analytics

Realize your potential by joining the leading performance-driven advertising company!
As a Product Analyst (Maternity Leave Replacement) on the Product Analytics team in our Tel- Aviv office, youll play a vital role in shaping product strategy through data and accelerating decision-making with AI-powered analytics. Youll partner closely with Product Managers to uncover opportunities, define success metrics, and transform complex data into actionable insights. By combining deep analytical expertise with modern AI tools, youll help build smarter products while making analytics faster, more scalable, and more accessible across the organization.

A growing B2B SaaS company is looking for an experienced Head of Data Science to lead its Data Science function and drive the next generation of AI and machine learning capabilities.

This is a strategic leadership role combining people management, hands-on problem-solving, cross-functional collaboration, and ownership of data-driven innovation across the organization.


Responsibilities:

Lead and mentor a global team of Data Scientists.

Define and execute the company's Data Science strategy.

Drive the development of advanced machine learning, optimization, and forecasting solutions.

Partner closely with Product, Engineering, Customer Success, and executive leadership.

Translate complex business challenges into scalable analytical solutions.

Support customer-facing initiatives and strategic engagements when needed.

Establish best practices for experimentation, model evaluation, and performance measurement

Act as a key stakeholder in shaping the company's AI vision and roadmap

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 our 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.

We are looking for a talented and experienced Data Scientist to join our Research Data Science team and play a key role in shaping the future of cloud-native network security. Your primary mission will be to lead the development and deployment of AI-driven capabilities that protect enterprise networks at scale through our companys SASE platform, powering core products such as our AI assitant, DLP, XDR, IPS, and more.
Leveraging rich, real-time data from our global backbone and Cloud data warehouse, you will apply advanced reserach analytics, machine learning, deep learning and GenAI techniques to solve complex cybersecurity and networking challenges.
This is an exciting opportunity to join a fast-growing company and drive innovation in the rapidly evolving SASE space.
Key Responsibilities
Lead the design, development, and deployment of AI/ML models that enhance our companys security and networking products
Leading networking and security research, including analysis of large-scale network traffic and security data to identify patterns, threats, and opportunities for product improvement
Research, fine-tune, and train models optimized for real-time inline inference under limited compute resources
Collaborate cross-functionally with product, engineering, and support teams to translate product and business needs into AI solutions
Define and track success metrics to ensure AI solutions meet performance and business goals.

We're looking for a Senior Car Insurance Pricing Expert to help shape how we price risk across our global business, from our Tel Aviv office.
This isn't a traditional actuarial role. You'll sit at the intersection of Insurance, Data Science, Product, Engineering, and Business Strategy on our Insurance team, owning hard pricing and risk-management problems end to end. That means finding opportunities, designing better approaches, building scalable tools with technical teams, and turning insights into decisions that move growth, profitability, and risk selection forward.
You might be a trained actuary, a pricing leader, a decision scientist, or a technically strong insurance operator who's built serious pricing capabilities. Formal credentials are a plus, but they're not the point. The point is whether you can use data, insurance intuition, statistical rigor, and AI-enabled tools to solve complex pricing problems better and faster than the industry standard.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role you'll
Own and evolve core components of Car pricing strategy, bringing analytical rigor and product-minded creativity to how we price risk
Identify high-leverage opportunities across rating, underwriting, segmentation, risk selection, growth, profitability, and portfolio management
Build, evaluate, and improve Car pricing and risk models using actuarial methods, machine learning, AI-enabled workflows, and strong business judgment
Partner with Data Science, Product, Engineering, Finance, and Growth to turn pricing ideas into scalable capabilities
Translate complex pricing problems into clear product and platform requirements, helping teams build internal tools that make better decisions faster
Define and track key metrics - loss ratio, rate adequacy, conversion, retention, segmentation lift, and model performance - to keep decisions grounded in real impact
Make complex actuarial and pricing concepts clear and actionable for technical and non-technical audiences alike, and help build pricing acumen across the Tel Aviv team

As our company continues to scale, were looking for a Product Data Analyst to join our Product team. In this role, youll blend strong analytical skills with operational execution to help our product and go-to-market teams make data-informed decisions. About 70% of your time will be spent analyzing product and customer data, building dashboards, and delivering insights that will shape the future of our product. The remaining 30% will focus on supporting our data operations - ensuring our data processes, tools, and reporting cadences run efficiently, implementing best practices.

Youll sit directly within the Product organization, collaborating closely with Product Managers, Designers, and Engineers to improve how we use data across a growing suite of B2B SaaS products and within our organization.

Responsibilities
Analytics
Analyze product usage and customer behavior across multiple SaaS products to uncover insights that guide roadmap priorities and growth opportunities.
Build and maintain dashboards and reports in Snowflake, Redash, Metabase, and Mixpanel using SQL to support Product, GTM, and leadership teams.
Define and track key metrics such as activation, retention, adoption, ARR growth, and engagement.
Run ad-hoc analyses to answer business questions and support experiments or feature evaluations.

Data Operations
Collaborate with Engineering and Data teams to enhance analytics setup and data workflows.
Partner with Engineering teams to ensure clean data instrumentation, event tracking, best practices for data, and measurement implementation across product features.
Maintain and improve data quality processes, pipeline documentation, and operational standards to support reliable decision-making.

we are looking for a Product Analyst.
the Product Analyst position directly affects the companys product decisions. Our growing Data department is looking for a highly motivated team player who is proactive, a problem solver, and a storyteller. You will play a key role in analyzing patterns, identifying trends, and providing insights that directly influence our product strategy and roadmap.
Responsibilities:
Act as the analytics partner for product managers from ideation through discovery, research, planning and analyzing A/B tests.
Analyze large and complex data sets using SQL and statistical methods to provide actionable recommendations for improvements.
Manage a full data collection life cycle - define, collect and process data.
Conduct deep-dive analysis of new features and A/B tests to validate hypotheses, monitor KPIs, and measure success.
Build robust, self-served dashboards, reports, and alerting to enable data-driven decisions across the team.
Conduct opportunity sizing and impact assessments to ensure the team focuses on the most meaningful features and initiatives.
Promote new tools and methods to make data-driven decisions.
Work closely with R&D to achieve data-related goals.
Share and present insights and data stories to a diverse set of stakeholders, including management.

We're looking for a Product Data Analyst to help us find the opportunities hiding in our data and turn them into real product improvements.
You'll be part of the Analytics team, embedded in product decisions from early question to final recommendation. You will be tackling analytical questions, monitoring the metrics that matter, and surfacing insights that actually change how we build
We believe three things matter for every role: drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Collaborate with Analytics, Product, and Data teams to sharpen business decisions.
Initiate analyses and generate reports for feature tracking, experiments, and product health monitoring
Design A/B tests across our flows and processes to build better products
Analyze data using Snowflake, Python, and other platforms
Present key findings to stakeholders across the company, turning data into clear, actionable direction
Map new data domains and identify signals that push our product forward

Reequired Product Analyst
Working in data is about finding what nobody else knew they lost. We want investigators, people who adapt, think flexibly, and know how to bring leadership onboard. From scientists to engineers to visualization experts, our data team is made for those who find the missing piece and act on it. So if curiosity is your default setting and making it useful your priority, the Data team might be what you're looking for.
Working in data is about finding what nobody else knew they lost. We want investigators, people who adapt, think flexibly, and know how to bring leadership onboard. From scientists to engineers to visualization experts, our data team is made for those who find the missing piece and act on it. So if curiosity is your default setting and making it useful your priority, the Data team might be what you're looking for.
What am I going to do?
Own analytics across core product areas and user flows
Analyze product performance and derive actionable insights
Plan, run, and analyze A/B tests end-to-end, including experiment design, metric definition, and impact analysis
Partner closely with Product Managers and Engineering teams as the data focal point for product decisions
Build and maintain analytical foundations, including tracking, events, funnels, and data processes
Proactively monitor key metrics, identify trends or anomalies, and communicate insights to stakeholders
Create visibility through reports, dashboards, and alerts to support ongoing decision-making
Lead deep-dive analyses and broader business research as needed.

we are looking for a Junior Fraud Data Scientist.
As a Junior Fraud Data Scientist, you will contribute to our ongoing efforts to protect our ecosystem from financial threats and abuse. Working under the guidance of senior team members in a data-rich environment, you will assist in identifying malicious behaviors, support detection coverage, and help maintain our automated mitigation strategies.
This role is designed for an analytical professional with 1-2 years of experience who wants to build a deep expertise in adversarial data, learn from an experienced team, and develop their technical skills across modern cloud data platforms.
What You Will Be Doing
Exploratory Data Analysis: Support the team by mining behavioral and transactional datasets to help identify anomalies and emerging fraud patterns.
Model Support & Optimization: Assist in building, tuning, and validating machine learning models (e.g., XGBoost, LightGBM) under the supervision of senior data scientists.
Feature Generation: Extract, engineer, and prepare new data features from structured and unstructured sources to help improve model performance.
Dashboarding & Monitoring: Build and maintain internal dashboards and pipelines to track model health, data drift, and key fraud KPIs.
Cross-functional Collaboration: Work alongside Fraud Analytics and Product teams to help translate operational fraud insights into automated data solutions.