דרושים » אלגוריתמים » DLP Next - Data Scientist

We are looking for a strong, hands-on Data Scientist to join a cutting-edge AI and cyber security initiative at Check Point.
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.

Key Responsibilities
Research and develop innovative AI-powered capabilities for cyber threat prevention.
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.

Join our AI & Innovation group as a Data Scientist and help shape the future of AI-driven security solutions. Youll work with a team of passionate, sharp-minded professionals tackling complex challenges at the intersection of AI, data science, and cybersecurity building the next generation of security products at the core of Check Points strategy.

Youll have access to some of the best cybersecurity data sources available, working in a fast-moving, dynamic environment that blends the agility of a startup with the scale and stability of a global leader.

If youre excited about solving real-world AI challenges, translating research into impactful solutions, and collaborating with top talent to push the boundaries of innovation we want to hear from you.

Key Responsibilities
Translate ambiguous product or business challenges into well-defined data science problems
Research and prototype cutting-edge AI techniques (LLMs, RAG, knowledge graphs, etc.)
Design and implement data-driven algorithms, analyze data, build and evaluate models
Collaborate with engineering to deploy scalable, production-ready solutions
Work with product teams to align AI solutions with user needs and business goals
Collaborate cross-functionally with engineers, product managers, and fellow scientists to bring research into production and deliver measurable impact
Stay current with advancements in AI/ML and generative AI, and actively contribute to innovation within the team and broader organization

Check Point is looking for a talented AI Data Scientist to join the Policy Insight R&D group.

Come and join a dynamic cyber security internal start-up group at Check Point, developing solutions based on Machine Learning to protect our customers.

We seek a strong, motivated, and highly technical researcher who can be part of the Innovation team.

With an R&D mindset, the research outcome will be integrated into our product.

The position allows gaining extensive knowledge about security-related issues based on Machine Learning algorithms that would help to secure organizational networks, including IoT devices.

You will be able to directly impact protections against major vulnerabilities.

Key Responsibilities
Be part of the Innovation team that is responsible for Check Points Policy Insights and IoT security solutions.
Build ML/AI solutions together with a strong partnership with our engineering team.
Work with data throughout the entire pipeline from Data Engineering and Data Analytics to ML/AI models.
Collaborate with all the data & research-related groups within Check Point.
Writing protections against various attacks and investigating IoT devices, and understanding their network footprints and integration with other systems.
Productization & development of technologies from the POC stage into an enterprise-scale security solution.
Work closely with other development teams, QA, product management, and customers.

Similarweb is the leading digital intelligence platform used by over 3500 global customers. Our wide range of solutions power the digital strategies of companies like Google, eBay, and Adidas.

We help our customers succeed in todays digital world by giving them access to data-driven insights, competitive benchmarks, strategic analysis, and more.

In 2021, we went public on the New York Stock Exchange, and we havent stopped growing since!

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 Similarweb?

Similarweb is 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

Meta is seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
Software Engineer, Machine Learning Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding

As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.

As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.

Our team focuses on developing foundation models for remote sensing (i.e., satellite, aerial) imagery. We aim to simplify and enhance various remote sensing tasks including land use/land cover segmentation, object detection, and change detection for use by Google teams and external partners. We also investigate natural language interfaces for remote sensing imagery through vision-language models and tasks such as captioning and visual question answering.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

Responsibilities
Explore research directions, generate hypotheses and perform rigorous experimentation in several sub-domains (e.g., pre-training recipes, multi-modality, temporal sequences).
Contribute to shaping the team's roadmap, help prioritize research directions, with focus on innovation and usability.
Work with other researchers across Google to connect multiple geospatial efforts.
Help teams use foundation models and optimize its use on their tasks.
Advise and mentor team members.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Financial Risk Management Machine Learning Principal Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. - Provide regular feedback to other engineers regarding their technical work