לוח משרות דרושים Data Scientist בתל אביב יפו

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

With an R&D mindset, the research outcome will be integrated into Checkpoint products.

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.
Developing and implementing protection mechanisms against diverse cyberattacks, while investigating IoT devices to analyze their network behaviours and integration within complex 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

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). 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 Meta, 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 Meta. 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