דרושים » תוכנה » Senior Product Data Scientist, Geo Data Science, Waze

Partner with Product, Engineering and User Experience (UX) research teams to provide investigative thought leadership, support metrics research and advanced statistical analysis of user journeys across GIE surfaces and Google products
Identify metrics improvement areas, design new metrics, and evaluation methods
Perform large-scale data analysis and modeling to identify opportunities for deepening the understanding of end-user behavior, product improvements and measure the impact of initiatives on top level KPIs
Use statistical methods to design and suggest experiments and new ways to establish causality, estimate impact and answer strategic questions using data
Support teams with advanced experimentation methods, detect user learning effects, and drive actionable user insights. Make product recommendations with presentations of findings for multiple levels of stakeholders.

We are looking for a Data Scientist- Autonomous.
The Research and Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more).
As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

We are looking for a Data Scientist.
The Data Science department plays a pivotal role in our company, generating value by developing algorithms and analytical production-grade solutions. We leverage advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, you will assume the classic data-science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, solid background in statistical modeling and machine learning, a technical data-savvy nature, along with a passion for problem-solving and a desire to drive data-driven decision-making.
What You'll Be Doing:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities

Required Data Scientist, Product Analytics
As a Data Scientist, 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 wide-range 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 us, 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 us. 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 broad 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
Defining new opportunities for product impact Influencing product and sales to solve the most impactful market problems
Apply your expertise in quantitative analysis and the presentation of data to see beyond the numbers and understand how our users interact with our growth products
Work as a key member of the product team to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches in partnership with Product, Engineering, and cross-functional teams
Set KPIs and goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics
Exploratory analysis to discover new opportunities: understanding ecosystems, user behaviors, and long-term trends Identifying levers to help move key metrics.

We're looking for a sharp and passionate Data Scientist to join our top-notch Data Science team.
Using your technical and analytical skills, your mission will be to develop Data Science models in purpose to directly impact the business KPIs in various areas.
Responsibilities:
Develop data science models to support business decision-making and improve KPIs across various areas.
Analyze complex data sets to identify trends, patterns, and insights.
Continuously monitor and improve model performance through testing and experimentation.
Execute projects end-to-end from requirements gathering, data mining, and exploration up to full implementing in production
Collaborate with cross-functional teams including product, engineering, and marketing to identify data-driven solutions.
Communicate findings and insights to non-technical stakeholders in a clear and concise manner.
Stay up-to-date with the latest advancements and trends in data science and machine learning.
Creating a framework of technical standards and procedures.

This is a unique opportunity to join an exciting early-stage startup experiencing hypergrowth in a white-hot segment of the cybersecurity space.
a fast-growing cybersecurity startup and the creator of the first comprehensive software supply chain security solution. As software supply chain attacks rise sharply, platform delivers complete visibility, security, and integrity across all stages of the software development lifecycle (SDLC), helping companies protect against high-profile threats.

Founded in 2019, backed by YL Ventures and Insight Partners and has received significant industry recognition, including Cyber Defense Magazine's Top Infosec Innovator (2023) and multiple other awards in recent years.

As a Data Engineer , you will play a pivotal role in shaping our evolving data culture. You will be responsible for collecting, organizing, and analyzing data to provide valuable insights that drive informed decision-making across the organization. This is a "one man show" position, meaning you will work independently to manage all aspects of data engineering, from data collection to analysis. This is an opportunity to join a dynamic team and contribute to the development of data-driven solutions that drive business growth and innovation. If you are passionate about data and thrive in a collaborative environment, we encourage you to apply.

Responsibilities
Collect and gather data from various sources, both internal and external.
Organize and clean datasets to ensure accuracy and reliability.
Utilize appropriate tools and software to analyze and visualize data effectively.
Collaborate with cross-functional teams to identify data needs and requirements.
Develop and implement data collection strategies to support business objectives.
Interpret data and provide insights to inform decision-making processes.
Create reports and presentations to communicate findings and recommendations.
Assist in the development of data-driven solutions to address business challenges.
Stay updated on industry trends and best practices in data analysis.

Were looking for a People Analytics Specialist to join us and spread the power. This role involves collecting, analyzing, and interpreting data on workforce trends to provide actionable insights that drive decision-making across the HR function.
WHAT YOULL DO
Collect and maintain accurate employee data from various HR systems (e.g., Workday, Greenhouse).
Analyze HR data related to recruitment, workforce planning, turnover, compensation, benefits, and performance.
Develop and deliver reports and dashboards to track key HR performance indicators (KPIs) and business trends.
Manage and analyze employee leveling data to ensure consistent application of job leveling across the organization.
Provide insights into compensation trends, including global market analysis, benchmarking, and support during annual merit cycles.
Collaborate with HR business partners and organizational leaders to provide data-driven insights that identify trends in employee behavior, retention, and engagement.
Work with HRIS team to enhance the functionality of HR systems and tools.

A global leader in performance marketing, is looking for a talented Data Scientist to join us on our mission to simplify decision-making for millions!
What You'll Do
Responsibilities
End-to-end project ownership with advanced modeling: Take ownership of projects from ideation and design to deployment, leveraging advanced machine learning and deep learning techniques to develop innovative solutions that address complex business challenges.
Data exploration and preprocessing: Gather, clean, and preprocess large-scale datasets from diverse sources, ensuring data quality and readiness for modeling.
Develop scalable production-ready code: Develop for both real-time and batch modeling pipelines, collaborating with data and engineering teams for seamless integration.
Innovation and research: Stay ahead of industry trends by exploring and applying cutting-edge advancements in data science, machine learning, and AI to solve emerging challenges.
Data visualization and insight communication: Transform complex analytical results into actionable insights through clear visualizations and articulate presentations for diverse audiences, including technical and non-technical stakeholders.
Collaboration across teams: Work closely with cross-functional teamsproduct managers, engineers, and business leadersto identify opportunities, prioritize initiatives, and deliver impactful results.

We are looking for an experienced Data Scientist who can leverage and develop innovative machine learning, NLP, and generative AI technologies, for solving problems within a wide scope.

As a part of our Data Science group, you will work on highly complicated challenges, from research to production, and help shape our algorithms and AI platform. You will work with Developers, Analysts, Product Managers, and business owners on growth opportunities and new ideas.

You should have a strong background and experience in the machine learning pipeline through business understanding, research, data exploration, feature engineering, model building, performance evaluation, testing, production-level code and deployment, model monitoring, and maintenance.

What am I going to do?
Take leading roles in projects such as search engine ranking, promoted ads in search results, recommendations, users segmentation and personalization, online bidding optimization, text analysis, real-time predictions, live streaming data handling, exploration-exploitation problems, etc.
Work closely with various departments in the company to provide advanced Data Science solutions end to end.
Write and own production models and code.
Independent research and innovation in new content and technological domains.
Lead and advise other team members.
Continuously produce new initiatives and improvement ideas.
Act as a leader of AI platform. Develop models and framework solutions for the group.