דרושים » הנדסה » Product Data Scientist (Customer-facing)

Were looking for a sharp and driven Data Analyst 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 Big Data Analyst 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

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.

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.

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 (Maternity leave).
As part of data team, you will be the gateway of data from multiple sources and of multiple partners. The data team is a part of research & data science department, and its mission is to integrate, align, analyze, and extract data to serve decision making processes across.
Responsibilities:
Define and implement data policies, logics, and structures that will best serve the companys capability to improve its modeling, business understanding, and strategic decision making.
Own and create end to end data products, from raw data to monitoring and analysis tools.
Write and execute complex SQL queries for data retrieval and alignment.
Prepare on demand data analysis and reports for various stakeholders including management using Python/SQL/other data analysis instruments, processing large and complex data sets.
Full responsibility for new partners' data integration process, including business requirements definition, data processing and verification.
Explore new data sources and communicate insights to partners, internal stakeholders, and management.
Work closely with cross-functional teams, such as research, engineering, product, and finance, to define business needs and design data models to serve them.
Gain a wide knowledge of operational, business, and technological activities in order to add value and support achieving goals.
Assist to create structured data processes that will enable the companys scalable growth.

we are looking for a Data Science Team Lead.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to extract maximum value from data of all shapes and sizes, including classification models, NLP, anomaly detection, graph theory, deep learning, and more.
Our models and algorithms are integrated into the critical path of product, helping to make thousands of decisions per second in real-time. All the capabilities we develop must meet production-grade requirements in both analytical and engineering standards.
As the Team Lead of a Data Science team, you will manage critical analytical initiatives for our suite of products, shaping the team's direction and focus. You will collaborate closely with Product Managers to influence the future of our product offerings and ensure alignment with company goals. You will need a holistic view of challenges and a keen understanding of the underlying goals of the department and company. In this role, you will lead the team, oversee their professional development, build effective collaborations with other departments, and bring measurable value to product through your team's efforts.

we are looking for a AI Solution Engineer.
The AI Solutions Engineer plays a critical, high-impact role in scaling our clinical AI solutions and ensuring the ability to deploy high quality products, monitor and support them in production.
This position requires strong software and data engineering skills to elevate our operational systems.
You will be responsible for independently driving complex E2E projects, demonstrating flexible thinking and making cost-effective decisions while balancing quality versus speed.
You will serve as a vital technical bridge, forming strong collaborations with both the R&D and Product organizations. Success in this dynamic and fast-driven environment demands a focused "getting things done" and "can-do" attitude to deliver value with speed and quality.
Responsibilities:
Automate and streamline AI operations - develop tools to automate AI deployment, data validation, and reporting for smooth production integration of AI solutions built by our research teams.
Act as the production technical expert - collaborate with Product and R&D teams during feature design to ensure production feasibility, scalability, and operational excellence.
Lead end-to-end tool development - gather requirements, design, implement, and deploy operational tools and pipelines in collaboration with cross-functional teams.
Drive engineering quality and play a key role in team member mentoring - uphold and develop engineering standards while fostering innovation.
Investigate and resolve complex data challenges - analyze and address production data issues, including data quality, availability, performance anomalies, and integration challenges.
Collaborate with customer-facing teams - understand real-world operational challenges, develop scalable solutions, and bridge the gap between customer needs and AI system behavior.
Ensure ongoing AI model reliability - design and implement mechanisms for monitoring data and performance degradation, and maintaining long-term model effectiveness.
Develop monitoring and analytics frameworks - create metrics and dashboards to track production health, data integrity, and AI performance across the deployment lifecycle.

abra professional services is seeking a Data Analytics Architect / Principal Data Engineer We are looking for a skilled Data Analytics Architect / Principal Data Engineer to lead the organization’s analytics data domain, design large-scale data architecture, build advanced analytical models, define organizational data modeling standards, and implement innovative AI and LLM-based technologies. This role requires deep expertise in data engineering, analytics, BI, SQL, PostgreSQL, data modeling, performance optimization, data governance, and the integration of AI tools into data engineering processes. A full-time hybrid position based in Central Israel. The first 4–6 months will be based in Tel Aviv, followed by a transition to the Lod area. The position includes 1 day a week remote. Key Responsibilities:
* Design and develop data architecture that supports large-scale analytics and business intelligence.
* Lead the design and implementation of complex data models and enterprise data modeling solutions.
* Define organizational standards, methodologies, and best practices in the data domain.
* Optimize database performance, analytical queries, and reporting processes.
* Lead LLM-based development and implement AI tools within data engineering processes.
* Mentor data engineers, conduct code reviews and architecture reviews.
* Collaborate with management and business stakeholders to build a technological roadmap.
* Establish frameworks for data quality and data governance.
* Lead initiatives to improve the reliability and stability of BI and analytics systems.
* Evaluate new technologies and lead the adoption of innovative solutions across the organization.
* Lead the design and implementation of end-to-end analytics platforms.

We are looking for a passionate Senior Data Scientist to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment. If you are experienced but still hungry to learn and impact - wed love to have you on our team!

What Youll Do:
Devise, initiate, manage and execute cutting-edge exploration and exploitation projects.
Apply your knowledge of Data Science, Machine Learning and AI-driven algorithms to create scalable data solutions.
Analyze extremely large (petabytes) and diverse datasets to solve complex problems, and develop automated, intelligent systems to address them.
Design, build and deploy AI/ML models (including predictive models, recommendation systems and generative AI solutions) to drive business impact.
Leverage modern AI tools and frameworks to accelerate research and production workflows.
Proactively seek growth opportunities aligned with core KPIs.
Enable real-time and near real-time data insights - instant data gratification guaranteed.

We are looking for a Data Scientist to join our team.

The ideal candidate is a highly motivated and self-driven individual with strong analytical and problem-solving skills. The Data Scientist will be responsible for analyzing data and developing models to help inform decisions and strategies for new products and business initiatives.


Responsibilities:
Work closely with stakeholders to understand business requirements and develop predictive models to detect fraud.
Develop and implement statistical models, machine learning and deep learning algorithms to solve complex problems in a production environment.
Perform exploratory data analysis and data visualization to gain insights and communicate findings.
Collaborate with cross-functional teams, including data engineers and software developers, to design and implement end-to-end solutions that can be deployed in production.
Implement advanced analytics tools and technologies to enhance reporting capabilities.