לוח משרות דרושים Data Scientist משרה מלאה

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.

Lead the end-to-end development of the companys business products.
Manage a team of developers and QA engineers in an agile environment, supporting their professional growth and development.
Drive technical features from design through implementation and code review.
Collaborate closely with cross-functional teams including Product and Customer Success to ensure delivery of high-quality, valuable products to our customers.
Own and promote architectural best practices across the companys business services.

This Senior Data Science Engineer role will focus on designing and implementing Networking solutions based on AI for both the enhanced monitoring of our data centers and the optimization of our networking products. Developing such platforms provides unique vital signs and uses them to identify performance degradation, component failures and abnormal usage patterns.
As a Senior Data Science Engineer in the Networking AI group, you will work closely with many different teams, solving problems with their engineering teams, and playing a key role in building successful solutions.
What You'll Be Doing:
We expect you to conduct in-depth analysis of datasets, raise and validate hypotheses, extract significant features, and build, train, and deploy models on top of them.
Design and implement high-performance algorithms and data structures applicable to large-scale datasets and distributed processing. You will own the optimization and refinement of models to meet production-level performance and accuracy.
Collaborate with cross-functional teams to help define and execute the technical strategy for integrating AI-driven monitoring and optimization into our networking systems.
Build and test prototypes to demonstrate proof-of-concept and present technical findings to stakeholders and team leadership.
Analyze technical trade-offs in different solutions and design and implement robust systems for improving the throughput of analytics on large data streams.
Lead the technical implementation and integration of data science models into production environments.

As a Data Scientist at our company, 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 our company, you will become part of a world-class 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 our company. 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
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Were looking for a Data Scientist to join our Data Labs department, which specializes in professional services for our super premium customers.
This role will report to our Datalabs Team Manager in the, R&D.
Why is this role so important at our company?
we are a data-focused company, and our unique AI and machine learning capabilities are the center of our business.
As part of this role, you will create data models that help analyze the petabytes of data we receive from various sources, and research and develop new features and capabilities for our product solutions
As a data scientist in the Datalabs team, 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 out-of-the box requests from customers who want custom digital insights. The Datalabs departments customer centric and business-oriented nature also means you will be supporting a team of data analysts and consultants who interact directly with customers. Together with them, you will translate the voice of these customers into best-in-class digital insights.
So, what will you be doing all day?
Your role as part of the R&D department, and as part of the Datalabs team means your daily responsibilities may include:
Working on versatile use cases within a dynamic, fast paced production environment
Strategic thinking and problem solving, with a strong business sense
Analyzing data from various sources, and turning it into usable input
Understanding various use cases from different customers, and creating models that can translate these cases into meaningful insights
Initiating newly defined tasks from exploration to proof of concept
Owning the finalization of defined tasks (from POC to deployment in production)
Collaborating with data engineers to make sure we reach the desired production results
Owning the ongoing validation process for existing metrics
Collaborating and brainstorming best practices with other teams within the R&D department
Deploying machine-learning models into production for an ongoing use.

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.

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.

About Us Biolojic Design uses AI to design groundbreaking therapeutics and is the first company to apply AI in the design of human antibodies. Combining computational biology and large molecule drug design, Biolojic uses its proprietary AI platform to design antibodies with new capabilities to cure life threatening and debilitating diseases, ushering in a new era of smart therapeutics. Position Summary As a Business Development & Strategy Student , you’ll work directly with the Senior Director of BD & Strategy to support projects that shape our company’s growth. This is a hands-on opportunity to learn how strategy, science, and business intersect in biotech. This is a part-time, on-site position based in our offices. Key Responsibilities Competitive Landscape Analysis and Industry Trends – track and analyze industry players, therapeutic modalities, and market trends in biologics and AI-driven drug discovery. Clinical Trial Tracking – monitor clinical development programs across antibodies, antibody-drug conjugates, and related modalities, with a focus on competitive intelligence. Data Synthesis & Presentation – create concise reports, presentations, and dashboards to support strategic decision-making by senior leadership. Cross-functional Collaboration – Work with both scientific and business team members to gather insights and align on analyses. Qualifications
* Current graduate (MBA, MSc) student or recent graduate in life sciences, biotechnology, bioengineering, data science, or business with a healthcare focus.
* Strong interest in biopharma, antibodies, and AI-driven discovery. Excellent analytical, research, and problem-solving skills ; ability to synthesize large amounts of information into actionable insights.
* Proficiency in Excel, PowerPoint, and literature/database searches (e.g., PubMed, ClinicalTrials.gov, GlobalData).
* Strong communication skills (written and verbal).
* Ability to work independently in a fast-paced, entrepreneurial environment. What We Offer Exposure to senior leadership and strategic decision-making in a biotech start-up. Hands-on experience at the intersection of AI, biologics, and business strategy.
* Opportunity to contribute meaningfully to a fast-growing company advancing next-generation antibody therapies.
* Mentorship and career development support.

We are seeking a talented and driven Senior Software Verification Engineer to join our innovative team and tackle SW verification challenges in the domains of high-speed networking and virtualization. You will play a key role in validating and testing complex software products that support the InfiniBand protocol, delivering advanced networking services for cloud, HCP machine learning, and AI workloads.

What Youll Be Doing:

Build automated verification tests in a simulated environment for high-end hardware and software.

Collaborate with multiple teams to understand new network technologies, ensuring accurate modeling of complex network behaviors.

Enhance product quality by improving test coverage and developing comprehensive verification strategies.

What will you do:
As Senior Data scientist at our company, you will shape the future of identity security and develop innovative AI/ML solutions that enhance security and protect the emerging agentic AI landscape in top organizations. Drive AI research and engineering to address evolving threats and protect critical digital assets effectively.
Drive AI/ML projects from research to production, leveraging advanced algorithms, LLMs, classification models, Unsupervised learning and optimization techniques to enhance cybersecurity solutions.
Model Building: Design, implement, and optimize machine learning models, including deep learning, using frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn.
Work closely with product manager, engineers, software architects and analysts to understand requirements, validate model assumptions, and deliver actionable insights.
Identify AI/ML impact opportunities and translate business needs into actionable roadmap items.
Stay current with the latest advancements in data science and apply best practices to ensure optimal performance.

As a Data Science Team Leader at our company, you will lead a high-performing team developing AI/ML solutions that secure the digital worlds most sensitive assets. Youll play a key role in driving innovation, productizing machine learning systems, and applying advanced modeling techniques to real-world cybersecurity challenges. In this leadership role, youll balance hands-on technical involvement with strategic oversight, guiding projects from research to production. Youll work closely with data scientists, engineers, analysts, product managers, and Cyber-Security researchers to build intelligent features across our copmpanys identity security portfolio.
Lead, mentor, and grow a team of applied data scientists working on machine learning models that power AI-driven cybersecurity solutions.
Own the end-to-end development lifecycle of AI projects - from exploratory research and experimentation through scalable deployment and optimization.
Partner with engineering and product leadership to define technical strategies, prioritize initiatives, and ensure successful model delivery.
Drive innovation across a broad spectrum of ML domains including supervised/unsupervised learning, anomaly detection and generative AI.
Provide hands-on guidance in model development using tools such as scikit-learn, PyTorch, TensorFlow, and Hugging Face.
Ensure high-quality execution through strong code review practices, reproducibility, and model evaluation frameworks.
Champion best practices in MLOps, data governance, explainability, and monitoring.
Keep pace with academic and industry advances and translate cutting-edge research into productized capabilities.

As a key member in our team, you will manage and lead quality assurance processes, provide actionable insights, and help streamline data monitoring and alert systems. If you have a passion for improving processes, and driving data accuracy in consumer intelligence, we want to hear from you!

Responsibilities:

In-Depth Data QA and Oversight: Continuously evaluate and improve data monitoring and QA processes to enhance team efficiency and data quality. Implement best practices and create standard operating procedures for data verification, analysis, and alert management.

Quality Assurance Supervision: Oversee the regular QA checks conducted on partnership intelligence dashboards to ensure data integrity and consistency. Take a proactive role in resolving discrepancies and ensure the timely delivery of accurate reports.

Data Analysis & Reporting: Lead the analysis of trends and patterns in affiliate performance data to uncover areas for improvement. Prepare and present findings to internal teams in an easily understandable format.

Alert Management Oversight: Supervise the alert management system to ensure relevant alerts are delivered accurately to clients in a timely manner. Work with the team to assess the impact of alerts and determine corrective actions based on client preferences.

Cross-Functional Collaboration: Work closely with internal teams to foster communication and collaboration, ensuring alignment between the QA team and other departments such as R&D.