דרושים » תוכנה » Data Scientist

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.

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

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.

Required Machine Learning Scientist II - GenAI models and applications
21539
Role Description
Leadership/Team Quote:
The Content Intelligence team builds the platform that processes millions of images and texts daily, enriching our catalog with advanced machine learning models for content understanding, classification, and personalization. These capabilities power smarter recommendations, improved search experiences, and intelligent chatbots and agents that enhance customer interactions. The team also plays a key role in the AI Trip Planner, a new Generative AI-driven project transforming how travelers plan their next vacation
Role Description:
As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

Required Data Scientist
About the Role:
Our algorithms team is responsible for all of the AI and algorithmic challenges the company is facing, tackling complex real-world problems that directly affect the companys success. As part of this group, you will help establish a new research area within the company, building AI workflows that digests a large amount of construction documents and models to help with one of the product core processes.
What Youll Do:
Take part in all development aspects-from design to production-of LLM-based workflows to digest information from a variety construction-oriented documents
Research, design, and integrate LLMs to deliver advanced automation and reasoning capabilities.
Develop datasets and benchmarks to evaluate and monitor LLM-based applications effectively.
Build LLM evaluation and optimization processes.

Were looking for a Data Scientist Expert to join us and spread the power. In this role, you will lead the next generation of Data Security Posture Management (DSPM) and Secret Detection. You will build the algorithmic engines that discover and protect the world's most sensitive information in the cloud, driving R&D initiatives to implement AI-driven solutions that tackle emerging threats and enhance our customers' security posture.
WHAT YOULL DO
Lead applied research for AI-driven features in our DSPM and Secret Detection domains
Conduct deep research and classification of sensitive data (PII, secrets) across complex structured and unstructured formats
Own the research lifecycle from raw data exploration and failure analysis to production-grade implementation
Identify and assess data security risks and use cases within cloud environments
Leverage LLMs to automate complex security research and enhance data classification at scale
Partner with Engineering, Security Research, and Product teams to define research goals and maintain production pipelines
Evaluate and optimize AI models and algorithms using real-world datasets to ensure high accuracy and scalability.

Required Data Scientist
Realize your potential by joining the leading performance-driven advertising company!
As a Data Scientist, youll play a vital role in turning algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
How youll make an impact:
As a Data Scientist, youll bring value by:
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more
Our tech stack:
Python, Java, TensorFlow, Spark, Kafka, Cassandra, HDFS, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker.

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.

We are seeking an experienced Data Team Lead to build, lead, and scale our data function. This is a hands-on leadership role that combines strategic thinking, technical excellence, and people management. You will build and manage a team of Data Engineers and Data Analysts, while working closely with senior management and cross-functional leaders to translate data into measurable business impact.
This role is ideal for someone who thrives in a fast-paced startup environment, enjoys influencing decision-making at the highest levels, and is passionate about embedding a data-driven mindset across the organization.
What You'll Do:
Lead and mentor the Data team, and support their professional growth while achieving impact goals of the marketing data structure such as: multi touch attribution model, creative analytics and automated data governance processes.
Define and own the data vision, roadmap, infrastructure, and best practices aligned with company objectives.
Act as a trusted data partner to executive leadership and senior stakeholders, influencing strategy through insights and analysis while promoting a strong data-driven culture.
Oversee the design, build, and maintenance of a scalable and reliable data warehouse.
Lead the design, implementation, and optimization of ETL/ELT pipelines to integrate data from multiple internal and external sources.
Ensure high standards for data quality, governance, integrity, and documentation.
Translate complex datasets into clear, actionable insights that support the different departments' needs and the company growth through operational excellence.
Support advanced analytics use cases including forecasting, experimentation (A/B testing), and performance measurement.
Review and elevate dashboards, reports, and analyses to ensure clarity, accuracy, and executive relevance.
Identify gaps in data collection and proactively propose solutions to improve visibility and decision-making.