דרושים » תוכנה » Data Science Team Lead

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.

we are looking for a Data Scientist.
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 provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Required Big Data Engineer Team Lead
We are an innovative technology company led by data scientists and engineers devoted to mobile app growth. Our proprietary ad platform is powered by machine learning and is constantly improving its distribution algorithms.
We deliver valuable results and insights for a fast-growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies.
Our state-of-the-art machine learning technology analyzes 50TB of raw data per day to produce millions of ad recommendations in real-time. This data is used to power our machine learning predictions, business-critical metrics, and analytics to power our decision-making.
As a Big Data Team Lead, you will lead a team focused on building scalable, algorithm-heavy data products rather than owning the underlying data infrastructure.
Your team will be responsible for implementing complex business and optimization logic-often incorporating multiple algorithms using Peta-Byte scale data processing (primarily PySpark). A core part of the role is ensuring these data products are explainable, observable, and trusted by Data Science, BI, Product, and business stakeholders.
You will work closely with the Data Infrastructure TL, Data Science, BI, and Product to turn advanced logic into production-grade, transparent, and measurable systems.
Responsibilities:
Lead development of scalable, algorithm-heavy data products using PySpark and Implement and maintain complex, multi-stage data flows with multiple interacting algorithms.
Translate business and algorithmic requirements into clear, testable data logic. Ensuring explainability of outputs through intermediate artifacts, metadata, and documentation & Defining and monitoring; observability signals for data quality, algorithm health, and business impact.
Mentor engineers on reasoning about complex logic, edge cases, and failure modes.

Were looking for a talented and driven Data Science to join our Data Science / Applied AI team in Tel Aviv.
Youll work alongside senior data scientists and ML engineers on production AI systems that directly impact clinical care.

This is a hands-on role. Youll contribute to real projects from day one: improving AI-powered services, building evaluation pipelines, working on data quality and processing, and supporting the infrastructure that keeps our systems running reliably at scale. We value people who can operate independently, learn quickly, and deliver quality work in a fast-moving environment.

Responsibilities
Contribute to our production AI services (Python)
Build and maintain evaluation frameworks and data pipelines
Conduct data analysis to support research, quality validation, and product decisions
Support model integration and deployment workflows
Collaborate with DevOps, QA, and Product teams on cross-functional deliverables
Document technical work and share knowledge with the team

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within our company to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with our company and we remain a trusted partner.
The gTech Ads Data Science EMEA team helps measure and optimize marketing ROI for our companys largest clients. We build bespoke models that address clients key business issues.
In this role, you will be responsible for applying best data science practices to solve our ads customers problems in marketing. You will be passionate about bringing the best of our companys Machine Learning (ML) capabilities to build solutions that address our customer's problem-space. You will be responsible for executing on gTechs strategy and goal to deliver applied data science to our company's largest ads customers.
Responsibilities
Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with Machine Learning and statistics.
Collaborate with customers to unpack their problems and identify the best statistical techniques that can solve the problem; own the development of a modeling framework.
Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger solution, collaborate with Product/Engineering teams to increase and optimize capabilities of our data scientist (DS) team, employing methods which create opportunities for scale, proactively helping to drive innovation.
Work with customer and internal teams to translate data and model results into tactical and insights that are actionable for decision.
Develop comprehensive understanding of our company data structures, and metrics, advocating for product changes where needed.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.
As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.
You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.
What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in our companys search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of our companys AI platform. Develop models and framework solutions for the group.

As a data scientist, you will work on the very core of the company. Part of your role will be to turn raw data into usable metrics and develop new models and statistical algorithms to support our business. Together with other Data Engineers and Product Managers, you will translate the voice of our customer into best-in-class digital insights.

Responsibilities:
Analyzing data from various sources and transforming it into actionable insights that directly drive business growth.
Building machine learning algorithms for bidding - using classification and clustering to optimize campaign performance.
Leveraging artificial intelligence (GenAI) techniques to query data for intelligent insights and automated decision-making processes, unlocking hidden value from data.
Leading tasks from exploration to proof of concept (POC) and ensuring smooth transitions to scalable production environments.
Collaborating with data engineers and product managers to ensure the delivery of high-quality production results.
Creating and owning key metrics while developing new models and capabilities for innovative product solutions.
Optimizing scalability and ensuring the performance of data pipelines and ML models, handling large-scale, dynamic datasets.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope. As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas. You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.

What am I going to do?:

* Take leading roles in projects such as search engine ranking, promoted ads in Fiverr’s search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
* Work closely with various departments in the company to provide advanced Data Science solutions end to end.
* Write and own production models and code.
* Independent research and innovation in new content and technological domains.
* Lead and advise other team members.
* Continuously produce new initiatives and improvement ideas.
* Act as a leader of Fiverr’s AI platform. Develop models and framework solutions for the group.

Equal opportunities:
At Fiverr, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace, from our community to our product. Fiverr is proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, Fiverr will provide accommodation to individuals with disabilities or a special need.

Required Software Engineering Team Lead
Were looking for driven and talented people like you to join our Sales team and our mission to change the future of cloud security. Ready to dive in and swim with our pod?
Highlights:
High-growth: Over the past six years, weve consistently achieved milestones that take other companies a decade or more. During this time, weve significantly grown our employee base, expanded our customer reach, and rapidly advanced our product capabilities.
Disruptive innovation: Our founders saw that traditional security didnt work for the cloud so they set out to carve a new path. Were relentless pioneers who invented agentless technology and continue to be the most comprehensive and innovative cloud security company.
Well-capitalized: With a valuation of $1.8 billion, we are a cybersecurity unicorn dominating the cloud security space. Were backed by an impressive team of investors such as Capital G, ICONIQ, GGV, and SVCI, a syndicate of CISOs who invest their own money after conducting their due diligence.
Respectful and transparent culture: Our executives pride themselves on being accessible to everyone and believe in sharing knowledge with the employees. Each employee has a place in shaping the future of our industry.
About the Role:
As a Team Lead on the Data Platform, youll guide one of our most strategic engineering groups - the team building and evolving the core data ingestion and processing infrastructure that powers our entire platform. Handling billions of cloud signals daily, the team ensures scalability, reliability, and efficiency across our architecture.
Youll lead a group of talented senior engineers, providing both technical and people leadership while staying hands-on in design and implementation. Together, youll drive key architectural decisions and evolve our ingestion and processing layers to support real-time pipelines, improve observability, and enable greater horizontal scalability.
Were looking for an experienced Team Leader eager to make a foundational impact on our next-generation cloud security data platform.
Our Stack: Python, Go, SingleStore, Postgres, Redis, Kafka, AWS.
What Youll Do:
Lead, mentor, and develop a team of senior software engineers through one-on-ones, feedback, and technical guidance
Own and drive the delivery of high-impact projects end-to-end, from design through deployment and production monitoring
Design and review architecture for large-scale distributed systems focused on data ingestion, normalization, and availability
Collaborate cross-functionally with Product, SRE, and other R&D teams to define priorities, interfaces, and success metrics
Ensure the reliability, scalability, and observability of core services, introducing SLOs and best practices for operations
Participate in incident management, postmortems, and continuous improvement initiatives
Foster a culture of technical excellence and accountability within the team
Write and review clean, maintainable, and tested, take part of the on-call rotation.

We are looking for a strong, hands-on Data Scientist with knowledge in Security Research to join a cutting-edge AI and cyber security initiative at our company.
In this role, youll be part of a growing data science team working on advanced prevention technologies, leveraging vast amounts of data and state-of-the-art machine learning techniques to help protect users on a global scale.
This is a unique opportunity to join a high-impact, research-driven environment, where you will have the chance to shape core components of a next-generation security solution.
The team is responsible for researching and developing state-of-the-art AI/ML engines that protect hundreds of thousands of customers worldwide.
Perform daily analysis of real-world malware campaigns observed in the wild.
Research and evaluate optimal modeling approaches to address new security enhancements.
Design and build high-quality datasets and train models to detect emerging and advanced malicious techniques.
Deploy models within our companys cloud infrastructure, capable of processing and analyzing millions of files per day.
Key Responsibilities
Research and develop innovative AI-powered capabilities for cyber threat prevention.
Perform hands-on malware analysis in Windows environments, focusing on files and related threats.
Rapidly prototype and iterate based on data insights and user feedback.
Design and build data-driven solutions with a strong emphasis on practical impact and performance.
Collaborate closely with cyber researchers, analysts, and engineers to deliver production-grade machine learning models.
Work across organizational boundaries to bring solutions from concept to large-scale deployment, considering system constraints and integration challenges.