לוח משרות דרושים Data Scientist

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 Googles 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 Google's largest ads customers.
The Business Operations and Strategy team at Google plays a critical role in defining and driving strategic, operational and organizational improvements across the company. Also known as "BizOps", the group operates like an internal consulting group working on a range of critical projects and issues. BizOps creates strategies for promoting growth of our products like YouTube, Chrome and Mobile. They handle issues around partner development, strategy work in emerging markets such as Africa and India, as well as pricing strategies across our B2B and consumer products. The BizOps team is at the forefront of Google's fast-moving strategic priorities, addressing operational challenges and enabling innovation.
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 Google data structures, and metrics, advocating for product changes where needed.

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