דרושים » תוכנה » Data Scientist AI Team

we are seeking a Senior Data Scientist to drive the development and implementation of AI-based solutions that solve complex business challenges across our innovative SaaS platform. In this key role, youll work cross-functionally to lead end-to-end AI projectsfrom data exploration to deploymenthelping shape the future of our intelligent products and user experiences.
If youre passionate about machine learning, LLMs, and real-world impact, and thrive in a collaborative, high-velocity environment, wed love to connect
What You Will Do:
Identify AI opportunities to enhance product experiences and operational efficiency.
Collect, analyze, and model diverse financial datasets to develop actionable AI Products.
Own the full AI solution lifecyclefrom problem definition to research, modeling, and hands-on implementation.
Break down complex problems into well-defined, structured work plans.
Collaborate closely with developers, product managers, and other stakeholders to integrate AI solutions seamlessly into products.
Stay up to date with AI, ML, and LLM trends, translating them into practical applications.
Provide technical leadership and mentorship to junior data scientists while balancing immediate delivery with long-term innovation.

Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of Lemonades data ecosystem.

The groups mission is to build a state-of-the-art Data Platform that drives Lemonade toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.

In this role youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams

Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights

Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance

Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights

Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions

Collaborate closely with other Staff Engineers across Lemonade to align on cross-organizational initiatives and technical strategies

Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions

Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization

As an AI Developer on our Optimization team, you will play a key role in advancing our core optimization capabilities by infusing them with cutting-edge artificial intelligence.

Our team is on a mission to significantly enhance our existing, high-performance optimization engine. You'll tackle a diverse range of complex problems - including optimization of vehicle routing and scheduling - for our customers at a massive scale.

You will join our team at a pivotal moment and be an integral part of building our next-generation AI/ML capabilities from the ground up. As a key contributor, your responsibilities will span the entire model lifecycle, from augmenting our current optimization models with advanced AI to implementing the infrastructure for their deployment and monitoring.

You will apply state-of-the-art techniques such as Deep Reinforcement Learning (DRL), predictive analytics, and Graph Neural Networks (GNNs), all while working with rich datasets including Geographic Information System (GIS) data.

Another core part of your role will be implementing best practices for safe AI/ML rollouts. You will help build and maintain robust A/B testing frameworks and canary deployment strategies, ensuring our innovations reach production safely and effectively.

In this highly collaborative position, you will work closely with other engineers and scientists, as well as cross-functional product teams in the US, to bring these intelligent services to life.

Responsibilities:

Develop, implement, and deploy state-of-the-art optimization models and machine learning algorithms to solve complex business problems like vehicle routing and resource scheduling.

Design and build robust, end-to-end MLOps pipelinesfrom data ingestion and feature engineering to model training, validation, and serving in a production environment.

Translate complex scientific concepts and research papers into production-quality code, primarily using Python and leveraging frameworks like PyTorch and optimization libraries.

Conduct rigorous offline and online experiments to validate model performance, ensuring that solutions are statistically sound, reliable, and deliver measurable business impact.

Were on a mission to revolutionize how marketers, writers, and innovators create their marketing content. With tools like ChatGPT?? taking the world by storm, its clear that the spotlight is now shining on the Generative AI space. However, its ultimate hurdle is now a self-compounding problem: with infinite options for messaging now available to all marketers how do we know what will actually work? Your words matter, and Anyword was built to ensure that they resonate. Since 2021, weve been building a platform to help both the worlds largest brands and its next rising stars actually move, inspire, and drive their audiences forward. In reality, weve removed the uncertainty of writing performance copy, and are the first to bring copy intelligence into play. Weve combined our own language models, predictive analytics, custom AI, and branding-specific tools to help brands rise above the noise in ways they couldnt before. Weve built the brain behind all marketing messaging, no matter where it lives and how you create it (with AI or not). And now were looking to you to help change the world with us!
About the role Anyword is seeking a senior NLP data Scientist to lead our marketing language predictive modeling. Youll explore complex datasets, build and fine-tune advanced NLP /LLM models, and partner closely with engineering and product to integrate your work into Anywords AI content platform.
Responsibilities:
* Define and own the technical strategy and roadmap for Anywords marketing language predictive modeling.
* Analyze, process, and derive insights from our ever-growing data resources.
* Solve challenging prediction problems by applying the latest ML/ NLP techniques to build and fine-tune highly performant LLMs.
* Collaborate with engineers and product managers to ship models end-to-end, from research to production.
* Monitor and iterate on models using offline and online metrics.

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 innovative 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.

This is a senior leadership role focused on technical excellence and innovation. You will mentor a talented team of engineers and scientists, guide the end to end technical strategy from innovative research to production deployment and ultimately define the art of the possible for our most critical operational systems.

Responsibilities:

Lead the design and architecture of complex, end to end AI systems, guiding projects from initial conception and research through to production deployment and impact analysis.

Own the technical vision for the next generation of intelligent automation, creating patented technologies that directly impact Salesforce Field Service's core competitive advantage and market differentiation.

Provide technical leadership and set the strategic direction for the research and development of novel optimization and machine learning solutions.

Drive fast paced experimentation by independently or collaboratively prototyping solutions that showcase how new AI technologies can address real world business challenges. Collaborate with cross functional teams to translate prototypes into actionable solutions and define incremental delivery plans for implementation.

Mentor and guide a team of AI developers and scientists, fostering a culture of innovation, technical excellence, and continuous learning.

Stay at the forefront of academic and industry advancements by attending top tier conferences, networking with experts, and continuously learning about the latest in optimization, AI, and large language models (LLMs) to identify, evaluate, and apply emerging techniques that drive a significant competitive advantage.
JR314441

Join the forward-thinking CloudGuard AI Security team, where youll collaborate with leading architects and engineers to design, build, and secure next-generation AI-enabled public cloud environments.
As a Data Scientist, you will not only build and refine machine learning models and analyze large-scale datasets but also take an active part in the coding effort and in developing production-grade components that power CloudGuards AI Security products.
Key Responsibilities
Develop AI Security Insights Leverage advanced statistical and machine learning techniques to detect threats, anomalies, or vulnerabilities in AI-driven cloud environments.
Build, Code & Optimize ML Solutions Design, implement, and optimize ML and LLM-based models using clean, maintainable, and efficient code; integrate them into CloudGuards product pipelines to ensure scalability and reliability.
End-to-End Product Development Collaborate with backend and DevOps engineers to deploy, monitor, and scale ML components within microservices and cloud infrastructure.
Data Exploration & Feature Engineering Conduct deep dives into complex datasets from various sources, transforming raw data into actionable features for robust model development.
Continuous Learning & Adapting Stay current on the fast-paced AI landscape, enterprise use cases, and emerging threat vectors; adapt existing models and pipelines accordingly.
Cross-Functional Collaboration Work closely with other data scientists, product architects, software engineers, and security experts to translate business needs into production-ready, data-driven solutions.

If you're looking for an exciting opportunity to make a significant impact and grow with a passionate team, we are the place to be.
What You Will Do:
Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, MLOps specialists, and analysts.
Design, build, and optimize end-to-end AI-driven features - from experimentation and model training to validation and deployment.
Develop production-grade code (Python and C#) to integrate advanced models and data-driven capabilities into our core products.
Continuously evaluate model performance and data quality in real-world settings, proactively driving improvements, retraining, and robust monitoring

Required Principal Data Scientist - LLM/GenAI (Cortex)
Your Career
Are you passionate about harnessing cutting-edge data science techniques to protect the world from cyber threats? Do you thrive in the dynamic world of cybersecurity? If so, we invite you to join our innovative and forward-thinking team, where you'll have the opportunity to shape the future of cybersecurity and impact millions of customers.
As a Principal Data Scientist, you will apply your expertise in data analysis, machine learning, and cybersecurity to build new defense techniques against cyber-villains. You will be a driving force in designing and developing groundbreaking, ML-based security solutions that block attacks even before they begin.
Your Impact
Contribute to a diverse and highly skilled research group that pioneers state-of-the-art technologies to protect our customers
Utilize analytical rigor, statistical methods, programming, and data modeling to analyze vast amounts of data, applying your cybersecurity knowledge to guide our focus and approach
Design and implement LLM-based solutions to face modern cybersecurity challenges
Decompose complex problems scientifically and provide actionable insights and recommendations to both technical and non-technical stakeholders
Lead and collaborate on end-to-end projects within the team and across engineering and product teams, from initial ideation to final deployment.

As a Data Scientist at our company, you will play a critical role in developing data-driven solutions that uncover legal insights at scale. Youll work across domains-analyzing large and complex datasets, designing models (including those based on LLMs), and translating data into actionable insights that support our mission of surfacing justice.
Youll take full ownership of your analyses and models, from problem definition to experimentation and evaluation. Youll collaborate closely with engineers, domain experts, and product teams to design robust data science solutions that create real-world impact and inform product decisions.
Responsibilities:
Design and implement data science solutions using LLMs and legal datasets to surface insights and automate tasks.
Lead end-to-end development of ML pipelines-from data exploration and preprocessing to model training, deployment, and monitoring.
Build and maintain production-ready pipelines for experimentation, evaluation, and inference.
Collaborate with legal stakeholders and analysts to define problems, identify opportunities, and translate them into data-driven solutions.
Develop and iterate on LLM-based systems, including prompt engineering.
Write clean, maintainable Python code that meets production standards, including testing and documentation.
Stay curious and proactive-evaluating new tools, approaches, and technologies.
Communicate clearly across technical and non-technical audiences, contributing to a collaborative team culture.