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Think of a startup inside a big company. With funding. At scale.

TeamUp (by AT&T) helps engineering leaders, managers, and developers improve daily.

Were building a big-data SW intelligence platform that turns data generated throughout the SW development lifecycle (code, user stories, pipelines, scanning tools) into insights and optimization tools to help 1000+ R&D teams in AT&T continuously improve while developing products for dozens of millions of customers to use.

We are looking for an experienced data engineer with a passion for engineering practices to join our team and help to redefine software excellence in the industry.

You will have an opportunity to own the whole data flow, from fetching the data and until visualizing it for users.

Your Responsibilities

Be responsible for designing the full data flow, from extraction to visualizing in external tools, implementing, and maintaining it
You will translate User and Product manager requirements into a technical design and implement it to be part of large data engineering solutions
Support robust, scalable solutions to enhance business analysis capabilities, identify gaps and design processes, and fill them
Work with cutting-edge big-data tools and techniques
Collaborate with R&D, architects, data scientists, analysts, Projects Managers and DevOps in order to deliver the right solution

A new team that provide valuable business and product insights for Field Operations that serve millions of customers.

The team will handle analysis of various KPIs including recurrent dispatched, technician utilization, route optimization and more.

It will involve measurement of many web and mobile applications to measure user-behavior, usage and efficiency.

We take responsibility for the entire process, from event definition and data engineering (including some ML) to visualization tools.

This role is for an individual contributor until a team is assembled.

Responsibilities:

Lead data analysis activity for several products and projects around in Field-Operations
Be the data focal point for various teams, providing insights and ideas for new functionality
Analyze and explore through large complex data sets representing key business drivers, trends and operational metrics
Conceptualize, create, automate and maintain dashboards for tracking key metrics and experiments
Proactively provide meaningful insights and actionable recommendations that drive decisions
Recruit new team members and mentor them

Financial Integrity is responsible for mitigating fraudulent and no-compliant financial activity in order to drive trust and integrity for all people and businesses using Metas financial ecosystem, while accelerating growth. Our team manages risk & compliance for Metas payment ecosystem across Facebook, Instagram, WhatsApp and Reality Labs, with direct impact on Meta's revenue.


Meta is seeking an experienced Data Scientist to join the Financial Integrity Data Science team. Our data science team works very closely with Product Managers, Data Engineers, Software Engineers, Economic Researchers, Compliance, and Risk Management to build intuitive, secure products to solve some of the most challenging problems, at a scale that few companies can match. This is technically challenging, will have massive global impact, and you will get to work closely with smart folks on an intellectually challenging initiative.

This is a full-time position based in our office in Tel Aviv, Israel.
Data Scientist - Financial Integrity Responsibilities
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.
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.
Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.

The product analytics team delivers valuable insights for data-driven decision for a mobile app that serves Millions of customers.

This application incorporates digital features related to Purchasing, Account Management, Billing and Payment and Support.

Our team oversees numerous business KPIs and employs cutting-edge tools and strategies.

We take responsibility for the entire process, from Event definition and data engineering (including some ML) to visualization tools.

Responsibilities:

Product-analysis activity for an application that serve millions of users
Analyze and explore through large complex data sets representing key business drivers, trends and operational metrics
Collaborate with data engineers to aggregate and clean large data sets in use
Conceptualize, create, automate and maintain dashboards for tracking key metrics and experiments
Proactively provide meaningful insights and actionable recommendations that drive decision

As part of Lite Interfaces team, youll be part in creating and improving products used by more than 1 billion users around the world, as well as driving growth for Metas family of apps through platforms such as SEO and paid marketing.

Our data engineers work cross-functionally with software engineering, data science and product management to provide the team with essential data needed for making strategic decisions, finding opportunities and answering crucial questions about our users and products.

As a data engineer, you'll have the opportunity to work with petabyte scale datasets and complex data models and logics, which youll then translate into efficient and scalable pipelines, tables and dashboards.
Data Engineer, Lite-Interfaces Responsibilities
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Optimize logging, pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact

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 diverse 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 developments 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.
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.