דרושים » תוכנה » Senior Data Scientist

We are looking for a visionary and technically versatile Data Science Manager to join the Data Science & MLE group within our DS & Analytics organization.
In this pivotal role, you will lead a hybrid team of Data Scientists and Machine Learning Engineers, acting as the bridge between cutting-edge technical innovation and high-level business strategy. You won't just be managing a team; you will be the Technical Lead defining how we solve complex problems-from predicting player behavior to optimizing marketing budgets using the latest in Generative AI.
You will partner closely with Game Directors, Product Managers, and our central analytics teams to drive value across Zynga's diverse portfolio. If you are a leader who is "bilingual" in data-possessing deep Data Science expertise to guide methodology while bringing high MLE and Engineering skills to build scalable, production-ready systems-we want to hear from you.
Key Responsibilities:
Team Leadership & Mentorship: Recruit, retain, and develop top-tier talent within the Data Science & MLE team. Foster an inclusive culture of innovation where technical rigor meets creative problem-solving.

Technical Direction & Engineering Standards: Act as the hands-on Technical Lead for the domain. You will supervise the end-to-end development lifecycle-from research to production-enforcing high standards and MLOps to ensure our models are scalable and maintainable.
Strategic DS & Analytics Support: Drive the development of advanced analytical frameworks to solve core business challenges. You will guide the team in applying rigorous statistical and machine learning methods to areas such as Time Series Forecasting, Causal Inference, Marketing Optimization, Root Cause Analysis, and more.
Strategy & Collaboration: Partner with Game Directors, BI Platform PMs, and embedded analytics teams to define the data strategy and roadmap. You will ensure that our technical initiatives are directly aligned with company-wide goals and solving the right problems.
Global Alignment: Maintain a tight collaborative network with Data Science & Analytics managers in North America, ensuring global consistency in methodologies, knowledge sharing, and joint development.

Were looking for a Data scientist Expert to join us and spread the power of our company. As a Data Scientist you will be responsible for driving research and development of autonomous AI agents and LLM-powered systems at our company. You will work closely with cross-functional teams to explore, innovate, and implement AI-driven solutions to tackle emerging threats, examine cloud security features, and enhance the companys security posture.
WHAT YOULL DO
Lead applied research on AI agents and LLM-driven features in the company platform - from autonomous threat investigation agents to AI-powered security operations workflows
Cover a range of features - from leveraging LLMs to enhance customer investigation experience to novel usage of AI for cloud security
Collaborate with engineering teams to design, build, and maintain production pipelines
Work closely with the Security Research and Product teams to define research goals
Conduct experiments and evaluate the performance of AI models, algorithms, and techniques using real-world datasets and simulated environments
Stay abreast of cutting-edge AI methodologies, frameworks, and tools and apply them to improve security solutions' accuracy, efficiency, and scalability.

Our algorithms group 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 a lead data-scientist, you will lead a new research area and a small team within the company. This is a primarily hands-on role where you will build the AI workflows that digest a large amount of construction documents and architectural models to help with one of the product core processes.
What Youll Do:
Lead and mentor a small team while remaining deeply hands-on in all development aspects-from design to production-of LLM-based workflows to digest information from a variety of 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.

Required Customer-Facing Data Scientist - Demand Forecasting
HQ in Tel Aviv with a growing sales and marketing organization in the US
Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson, Mars, and SciPlay.
Demand Forecasting Team:
The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients business success.
Responsibilities:
As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will:
Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models.
Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling.
Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business.
Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not.
Be instrumental in helping our clients achieve their business goals and realize the measurable value of our Demand Forecasting module.
Work within a production and product-oriented environment, ensuring models are robust, scalable, and directly integrated into the clients operational workflow.

We are looking for a Senior Data Products Manager to lead the strategy and evolution of our external data products, with a strong focus on customer needs and scalable, high-impact data solutions.
In this role, you will work directly with customers and internal stakeholders to understand how our data catalog is used across different use cases. Youll translate customer insights, usage patterns, and commercial input into a clear product vision and prioritized roadmap aligned with company objectives.
You will work closely with customer-facing data scientists and internal delivery teams to turn customer needs into production-ready data products. This includes collaborating with Partnerships to evaluate external data providers and defining requirements that guide the transformation of raw data into reliable, high-quality signals. You will also engage with the data pipeline itself, where different models are used to turn raw and unclassified data into coherent, scalable data products.
Responsibilities:
Own the strategy, vision, and roadmap for Exploriums external data products, guiding a delivery team of data developers and a team lead.
Lead customer discovery and translate insights into scalable product initiatives, requirements, and clear delivery plans.
Drive prioritization across competing needs, balancing customer value, business impact, feasibility, and time-to-market.
Lead the end-to-end data product lifecycle: discovery, definition, delivery, launch, adoption, and continuous improvement.
Collaborate cross-functionally with Data Science, Engineering, Sales, CS, and Partnerships to validate use cases and define measurable product success.
Write clear product specs and actionable tickets that guide the transformation of third-party data into production-grade data products.
Continuously improve existing products to expand coverage, improve accuracy, and unlock new customer use cases.
Define and track success metrics such as adoption, customer impact, accuracy, coverage, and performance.

about the job
the growth and notifications (gant) data science team's mission is to deliver the best of google's products to our users by enabling high-quality notifications and driving growth across the ecosystem. we are a team of data scientists and analysts who work to embed a deep empirical understanding of user behavior into the product development lifecycle. this enables our product partners to take smarter risks and build more engaging, high-quality experiences that drive sustainable growth.we are part of the broader ecosystem growth (eg) data science team within google identity and engagement (gie). our work is pivotal in increasing the number of users who experience the full value of google.this is an exciting opportunity to join a team that is at the forefront of driving user engagement and ecosystem growth at google.
responsibilities
lead large-scale data analysis and novel modeling approaches to create a deep understanding of user behavior with notifications and proactive agentic experiences.
partner with product, engineering, and UX research to define and develop novel evaluation metrics, validation methodologies, and experimentation frameworks for proactive quality models and ai-driven notification agents.
provide analytical thought leadership and advanced statistical expertise on user journeys, engagement models, and long-term causal effects across the gie and google ecosystem.
translate complex findings into actionable product recommendations, effectively presenting to cross-functional stakeholders at all levels to influence the product roadmap.
define, implement, and own key metrics to measure the quality, impact, and value of notifications and user-state models.

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.

Were looking for a Senior Data Science who is excited about designing and building production-grade AI systems powered by modern LLMs and machine learning.

This role is ideal for someone who enjoys working at the intersection of AI, engineering, and product, and who is passionate about turning cutting-edge AI capabilities into reliable, scalable systems that solve real customer problems.

Youll work closely with product managers, data scientists, and engineers to design, build, and deploy AI-powered solutions - including LLM pipelines, agents, and intelligent automation systems that power our core products.

This is a hands-on role where youll take ownership of the full lifecycle of AI features - from problem framing and architecture design to deployment, evaluation, and iteration in production.

Responsibilities:
Design and build AI-powered systems that leverage LLMs, embeddings, and modern NLP techniques to transform raw product data into structured, actionable insights.
Develop and maintain production-grade AI pipelines including prompt workflows, agents, retrieval systems (RAG), and automated decision processes.
Work closely with product and engineering teams to translate business needs into scalable AI solutions.
Architect systems that combine LLMs, data pipelines, and traditional ML into robust end-to-end products.
Experiment with and integrate new AI tools, models, and frameworks to continuously improve system capabilities and performance.
Own the full lifecycle of AI features - from design and prototyping to deployment, monitoring, and iteration.
Ensure reliability and performance of AI systems in production, including evaluation frameworks, guardrails, and monitoring.
Collaborate across teams to define best practices for AI system design, prompt engineering, and agent orchestration.
Collaborate closely with cross-functional team members, effectively communicate complex ideas, share knowledge, and mentor engineers and data scientists to elevate team standards and impact.

we are looking for a Senior Machine Learning Scientist I.
As a Senior Machine Learning Scientist, you will work closely with engineers and to design, develop, and evaluate machine learning solutions for scalable, customer-facing GenAI applications. Your work will focus on researching, training, fine-tuning, and rigorously evaluating models leveraging LLMs, recommendation systems, and agent-based architectures, using state-of-the-art techniques. You will drive experimentation, define success metrics, and translate insights into impactful AI solutions that shape the future of intelligent travel products.
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.

We are looking for a native French speaker with a high level of proficiency in English to join our Annotation and Analysis team at the as a Data Annotator and Analyst.
In this role, you will work with large volumes of data in both French and English, annotating and analyzing datasets used to evaluate and train machine learning models, including large language models (LLMs). Your work will involve reviewing model outputs and preparing high-quality training data that supports the development and continuous improvement of AI-driven products. In addition, as part of the job, you will conduct complex analysis on the annotated data and provide insights to the other stakeholders.
This position is ideal for someone passionate about linguistics and data, and who enjoys working on detail-oriented tasks that directly impact model quality. As part of a collaborative, cross-functional team, you will work closely with Data Scientists and Product Managers to ensure that datasets are accurately labeled and annotation standards support the development of reliable machine learning systems.
Responsibilities :
Evaluate the quality of machine-translated text, with a focus on French language accuracy and fluency.
Annotate and assess AI model responses to support systematic evaluation and improvement of model performance.
Create high-quality annotated datasets used to train and evaluate LLMs and other NLP models.
Write and refine LLM prompts that support scalable human annotation workflows.
Collaborate with cross-functional teams, including Data Scientists and Product Managers, to communicate linguistic nuances and implications of French translations on model behavior and user experience.
Analyze annotated data and evaluation results to identify patterns, assess model quality, and surface insights for model improvement.