TEGNA Inc. helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across web, mobile apps, streaming, and linear television, while also maintaining a strong global presence in India with offices in Bangalore and Chennai that support technology, product, and business operations initiatives. Together, we are building a sustainable future for local news. About TEGNA TEGNA Inc. (NYSE: TGNA) helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across the web, mobile apps, streaming, and linear television. Together, we are building a sustainable future for local news. Data Scientist TEGNA is seeking a highly skilled, innovative, and analytical Data Scientist to lead end-to-end development of advanced models and insights across our multi-platform media ecosystem spanning TV, digital, streaming, social, and mobile. This role is central to transforming large-scale viewership, content, and sales datasets into predictive models, optimization frameworks, and actionable insights that support content strategy, personalization, audience growth, and revenue performance. The ideal candidate is passionate about experimentation, machine learning, and building scalable data and ML solutions. You will collaborate with engineering,product, editorial, sales, and analytics teams to translate complex, ambiguous business challenges into measurable, data-driven outcomes. What You’ll Do Lead the full data science lifecycle: problem framing, hypothesis development, feature engineering, model development, validation, and deployment planning. Develop and operationalize machine learning models across forecasting, personalization, c
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Work Experience Required: 8 - 12 Years Experience in programing (Python, R, SQL, NoSQL,Spark) with ML tools & Cloud Technology (AWS, Azure, GCP) Experience in Python libraries such as numpy, pandas, scikit-learn, tensor-flow, scapy, scrapy, BERT etc. Good understanding in statistics, and ability to design statistical hypothesis testing to aid formal decision making. Develops predictive models using Machine Learning algorithms (SVM, Random Forest, Neural Network, Decision Tree, Logistic Regression, K-mean Clustering, linear regression, PCA etc.) Engaging with clients, understanding complex problem statements, and offering solutions in the domains of Retail, Pharma, Banking, Insurance, etc. Contribute to internal product development initiatives related to data science. Develop data science roadmap, and guide data scientist to meet their deliverables. Handling end-to-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction. Proven ability to discover solutions hidden in large datasets and to drive business results with their data-based insights Drive excellent project management required to deliver complex projects, including effort/time estimation. Be proactive, with full ownership of the engagement. Build scalable client engagement level processes for faster turnaround & higher accuracy Define Technology/ Strategy and Roadmap for client accounts, and guides implementation of that strategy within projects Run regular project reviews and audits to ensure that projects are being executed within the guardrails agreed by all stakeholders Manage the team-members, to ensure that the project plan is being adhered to over the course of the project Manage the client stakeholders, and their expectations, with a regular cadence of weekly meetings and status updates. Build a trusted advisor relationship with the IT management at clients and internal accounts leadership. Build
About the Team OpenAI’s People team hires, engages, and retains world-class talent to safely build and deploy AGI that benefits all of humanity. The People Analytics team helps leaders make rigorous, evidence-based talent decisions and ensures that the systems supporting those decisions are valid, reliable, fair, and accountable. About the Role As a People Data Scientist focused on AI fairness and bias testing, you will help establish how OpenAI evaluates AI-assisted People systems and high-impact talent processes. You will design and conduct rigorous assessments to identify, measure, and mitigate potential bias across the lifecycle of models, agents, decision-support tools, and automated workflows. Your work will span the entire employee life-cycle, such as hiring, performance, promotion, employee development, workforce planning, etc. You will evaluate both technical systems and the broader human-AI decision processes in which they operate, examining not only model performance but also data quality, measurement validity, differential outcomes, human oversight, and unintended consequences. We’re looking for an experienced data scientist or applied researcher who can translate complex fairness questions into defensible evaluation strategies, scalable testing infrastructure, and clear recommendations for technical teams and senior leaders. This role is preferred to be based in San Francisco, CA. In this role, you will: Define and lead fairness and bias-testing strategies for AI-assisted People processes, models, agents, and decision-support systems from development through deployment and ongoing monitoring. Design rigorous algorithmic audits and validation studies, including adverse-impact analysis, subgroup and intersectional evaluation, error-rate analysis, calibration, measurement invariance, reliability, criterion-related validity, and sensitivity testing. Identify the appropriate fairness criteria for each use case, evaluate tradeoffs among competing definitions
Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Auth0 is an easy-to-implement, authentication and authorization platform designed by developers for developers. We make applications’ login boxes safe, secure, and seamless for anyone logging in. The Auth0 Data Engineering Team Within Auth0, the Data Engineering team builds solutions to support analytics needs for the whole organization and is in charge of the Data Platform. It is divided into 3 groups: Pipeline team , sitting closer to the Platform team and data producers and in charge of the efficient data ingestion and provision of quick access to unmodeled data Warehouse team sitting closer to the business teams and data consumers and in charge of modeling the data in the data warehouse to abstract away the complexity for data consumers, simplifying the organization’s analysis, reporting and decision-making Interface team responsible for creating and managing connections between the data platform and various external systems (internal or external facing), making sure everyone has access to consistent and reliable data The Senior Data Engineer Opportunity Reporting to the manager of the Data Engineering Pipeline team, the senior data engineer will be a key player in ensuring the reliability and efficiency of our core data platform. This role is crucial, providing the stable data foundation that not only 'runs the business' day-to-day but also directly empowers the organization to unlock growth and build innovative new products. We are looking for an auto
Who We Are At Justworks, you’ll enjoy a welcoming and casual environment, great benefits, wellness program offerings, company retreats, and the ability to interact with and learn from leaders in the startup community. We work hard and care about our most prized asset - our people. We’re helping businesses get off the ground by enabling them to focus on running their business. We solve HR issues. We’re data-driven and never stop iterating. If you’d like to work in a supportive, entrepreneurial environment, are interested in building something meaningful and having fun while doing it, we’d love to hear from you. We're united by shared goals and shared motivations at Justworks. These are best summed up in our company values, which are reflected in our product and in our team. Our Values If this sounds like you, you’ll fit right in. Department Technology, Data & AI About The Team The Data & Analytics team is Justworks' data and AI center of excellence — a connected set of functions spanning business intelligence, data science, analytics engineering, platform data/ML engineering and AI builders. We've grown significantly over the last several years and continue to build momentum across the business, leveling up maturity in how we deliver insights, govern data, and enable the company to make better decisions. You'll find a highly collaborative & diverse group motivated by craft, shared learning, and a genuine commitment to growing our impact for customers while evolving how we work together for our people. Come build with us! The Data Platform Engineering team sits at the core of this foundation, owning the pipelines, platform infrastructure, and reliability that every other DNA function depends on. Who You Are You're a hands-on engineering leader with deep experience building and operating modern data platforms. You've led teams through scale — evolving architecture, improving reliability, and making hard tradeoffs between speed, cost, and quality. You're as
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of new features. The Global Growth team is at the forefront of innovation at Lyft, focused on expanding Lyft beyond North American rideshare’s core products. This includes our premium Luxury modes and Livery drivers, building a unified Lyft presence internationally, and enabling Autonomous Vehicles (AVs) domestically and abroad. These teams are at the center of innovation and the future of Lyft’s growth, and this role would be directly shaping the strategic roadmap for these crucial areas. As an Analytics Lead, you will collaborate with our world class team of engineers, product managers, and designers to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. This role will help define Lyft’s strategy for growing luxury modes, setting the strategic roadmap for pricing, driver pay, and product development. In this role, you will help us tackle problems such as: How should we be pricing our premium Luxury products? Who are our current Luxury riders and what segment is most likely to grow our rider base? How can we best merchandise Luxury rideshare products within the Lyft app? What product features or app changes would improve the rider experience and motivate riders to take more Luxury rides? How do coupons and incentives motivate riders and drivers in premium segments? What
At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Safety and Customer Care (SCC) team at Lyft manages over 1.7 million monthly human and AI interactions and serves as Lyft's primary direct touchpoint with riders and drivers. We handle critical infrastructure that powers both human associates and AI agents to make riders and drivers feel safe and comfortable while riding or driving with Lyft, transforming every support interaction into a moment of genuine connection. As a Data Engineer on the SCC team, you will have ownership over the data modeling and pipelines that power SCC’s Associate and AI Agent Platform . Your efforts will be critical to the reliability of our pipelines, execution of third party data integrations, accurate reporting of agents performance, and efficiency improvements that can save millions of dollars / year. You will work cross-functionally to bridge Lyft's business goals with data engineering. Your efforts will allow access to business and user behavior insights, using huge amounts of Lyft data to fuel several teams such as Analytics, Data Science, Engineering, and many others. Responsibilities: Owner of the core data pipeline, responsible for scaling up data processing flow to meet the rapid data growth at Lyft Evolve data model and data schema based on business and engineering needs Implement systems tracking data quality and consistency Develop tools supporting self-service data pipeline management (ETL) SQL and MapReduce job tuning to improve data processing performance Write well-crafted, well-tested, readable, maintainable code Participate in code reviews to ensure code quality and distribute knowledge Collaborate cross-functionally with product, engineering, data science, and marketing teams to understand business problems and align on prioritization and solutions Experience: Bachelor's degree in Compute
About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee
Who We Are Notion is the collaborative AI workspace where teams and agents think together . We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role: You're joining Notion's People Analytics & Operations team as part of an 18-month rotational program -- the group that builds the insights engine powering every people decision Notion makes. We look for slope over intercept. We care less about where you trained and more about what you've built. If you've ever rebuilt a broken process because it was bothering you, used AI to do something you couldn't have done alone, or found yourself reading about labor economics for fun -- you're the person we're looking for. Over 18 months, you'll rotate across people operations, people analytics, and compensation/benefits. Every rotation is real work with real ownership. On the analytics side, you'll build dashboards that land in exec review, write SQL that powers headcount models, and prototype AI-assisted workflows that help our team move faster. On the operations side, you'll run the HR engine -- managing employee lifecycle transactions in Workday, owning onboarding and offboarding coordination end-to-end, triaging and resolving employee requests, and keeping our people data clean and audit-ready. You'll be paired with a sen
About the Role We are looking for a seasoned Engineering Manager to lead our Data Platform. You will own the architecture and evolution of a Petabyte-scale Data Lakehouse and a Self-serve Analytics Platform, enabling real-time decision-making across the organization. In this role, you will drive consistency and quality by defining the right engineering strategies. You will oversee multiple engineering projects, ensure timely execution, collaborate across functions, and mentor engineers to grow into high-performing contributors.
TaylorMade Golf is a global leader in golf equipment, driven by relentless innovation across clubs, balls, and accessories. Our North America Operations team balances service, demand, and supply across a fast-moving, seasonal portfolio. The Senior Manager, Supply Chain Analytics & S&OP is the analytical backbone of TaylorMade's North America Operations team. This role sits at the intersection of Sales, Supply Chain, Finance, and Operations — translating complex data into clear, actionable insights that drive cross-functional alignment and continuous improvement across the S&OP cycle. This individual provides leadership visibility into key performance trends through reporting, data validation, and analysis across planning, service, inventory, logistics, and operations. They also lead and develop a team responsible for delivering accurate analytics and strengthening business intelligence capability across the North America Operations organization. Essential Functions and Key Responsibilities: S&OP Analytics & Process: Supports the North America S&OP process by preparing analytics and review materials that align Demand Management, Supply Planning, Sales, Finance, and Operations around demand, supply, service, and inventory considerations. Directs the team's preparation of pre-read materials, variance narratives, and executive-level presentations for monthly S&OP cycles, lessons-learned reviews, and consensus forecast sessions. Develops scenario and trade-off analysis for executive reviews to support decisions on capacity allocation, product priorities, service levels, and inventory balance. Partners with Sales, Demand Management, and Supply Planning to identify root causes of forecast bias, service performance gaps, and planning misalignment. Contributes to S&OP process maturity initiatives — documentation, playbook development, gover
About us: Working at Target means helping all families discover the joy of everyday life. About Target As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers. Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. At Target, we have a timeless purpose and a proven strategy. Some of the best minds from different backgrounds come together to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. Target in India operates as a fully integrated part of Target's global team and supports the company's global strategy and operations. About the team The IT Data Platform (ITDP) team enables data-driven management of Target's technology ecosystem by bringing together trusted data and insights across technology assets, software delivery, infrastructure, reliability, security, engineering effectiveness, and technology operations. The Analytics team within ITDP transforms this data into metrics, analytical products, dashboards, predictive insights, and decision-support capabilities that help technology teams understand what is happening, why it is happening, where risk may be emerging, and where action is needed. The team is building towards an analytics capability that progresses from descriptive and diagnostic analytics to predictive and prescriptive insights, using statistical methods, applied data science, and GenAI where each approach is appropriate. <p style="color:!im
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Staff Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Staff Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Staff Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Staff Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patterns. The id
What if the work you did every day could impact the lives of people you know? Or all of humanity? At Illumina, we are expanding access to genomic technology to realize health equity for billions of people around the world. Our efforts enable life-changing discoveries that are transforming human health through the early detection and diagnosis of diseases and new treatment options for patients. Working at Illumina means being part of something bigger than yourself. Every person, in every role, has the opportunity to make a difference. Surrounded by extraordinary people, inspiring leaders, and world changing projects, you will do more and become more than you ever thought possible. Summary The Staff Data Engineer is a seasoned, hands-on engineer who designs, builds, and scales data products on our cloud lakehouse, powering analytics, reporting, and AI/ML across Illumina. We are looking for someone with strong proficiency in Python, SQL, and data modeling, a solid understanding of distributed systems and system design who has built and scaled data products on modern cloud platforms such as Databricks and Snowflake. This is a hands-on, senior individual-contributor role with end-to-end ownership and leadership spanning multiple domains such as Supply Chain, Manufacturing and Quality, including mentoring engineers on our global (India-based) team. Responsibilities Partner across business, AI, and platform teams translating domain needs (e.g., SAP, Manufacturing, Quality) into well-modeled, governed and scalable data products. Design, build, and scale end-to-end data products on Databricks (and interoperating with Snowflake) — from ingestion through curated, analytics-ready datasets following a medallion (Bronze/Silver/Gold) architecture. Develop reusable frameworks, libraries, and
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Senior Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Senior Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Senior Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Senior Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patter
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