What is PerfectServe? PerfectServe is a leading provider of clinical communication and physician scheduling solutions in the health IT space. The company was founded in 1997 and has grown steadily since then, with a notable jump after several major acquisitions were announced in 2019. PerfectServe now has 400+ employees, 30,000+ customers — spanning medical practices, hospitals, and health systems — and $100 million+ in annual revenue. PerfectServe’s mission is to accelerate speed to care by optimizing provider schedules and routing communications — including messages, pages, calls, and alerts — to the right place at the right time in any care setting. By facilitating real-time information sharing, building better schedules, and automating important clinical workflows, we believe we can help our customers advance patient care and improve the well-being of their clinicians. Leading analyst firms like Gartner® and KLAS Research have consistently validated our approach: In 2026, PerfectServe was named highest in execution and furthest in vision in the Gartner Magic Quadrant™ for Clinical Communication and Collaboration — the clear segment leader. PerfectServe also received two Best in KLAS awards in 2026 — one for physician scheduling and another for ambulatory clinical communications. That makes for 11 Best in KLAS awards over the past 9 years. At PerfectServe, you'll have a unique opportunity to join a collaborative team with decades of experience that finds new ways to delight our customers every day. This involves consistent efforts to stay on the cutting edge of product development, which includes everything from implementing AI in new and existing solutions to brainstorming with customers about novel workflows. But you don't have to be in product to make in impact — everybody at PerfectServe contributes to important work that moves the business forward. If you're looking for a well-established, tech-forward company full of smart people doing meaningful work
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Since we opened our doors in 2009, the world of commerce has evolved immensely, and so has Square. After enabling anyone to take payments and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, offer buy now, pay later functionality, book appointments, engage loyal buyers, and hire and pay staff. Across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow in one place. Afterpay furthers our goal to provide omnichannel tools that unlock meaningful value and growth, enabling sellers to capture the next generation shopper, increase order sizes, and compete at a larger scale. Today, we are a partner to sellers of all sizes – large, enterprise-scale businesses with complex operations, sellers just starting, as well as merchants who began selling with Square and have grown larger over time. As our sellers grow, so do our solutions. There is a massive opportunity in front of us. We’re building a significant, meaningful, and lasting business, and we are helping sellers worldwide do the same. The Role We are looking for a quantitative, AI-fluent early-career professional to fill a data science role focused on payments data across Square and Cash App. You will partner closely with Product, Operations, Finance, and Engineering, leveraging data tools to optimize our payments platform from success rate, to cost efficiency, to risk mitigation. In addition to vertical work focused on the Payments domain, we also expect you to contribute to horizontal initiatives across the broader Data Org from data systems, to process and tooling. You Will Leverage AI to create scalable data tools, agents, and automations Partner with Product, Engineering, Finance, and Operations teams to systemize and make data-driven deci
Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase our speed, frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering, product analytics, experimentation, causal inference, statistical modeling and machine learning. Aligned and partnering with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure impact on our community of players and developers. WHY ENGINE INFRA? Engine Infra team is responsible for the game-server fleet that simulates live experiences — making it efficient, observable, and reliable on Roblox edge infrastructure and regional cloud capacity, from multiplexing and ARM bursting through telemetry, resource allocation, and edge latency. You Will: Define Metrics — Own Engine Infra metrics, telemetry logging, and validation for the RCC fleet and edge compute. Establish KPIs for game-server efficiency, reliability, and player experience — including C
About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. Data at GoCardless You'll sit in our Data and Business Systems group, working with technical and non-technical people across the whole company. You'll be part of a collaborative data engineering team, working closely with analytic engineers, analysts, and business stakeholders to deliver data solutions that scale with our rapidly growing business. We're a large team with an extensive remit, and we expect every member to work with initiative and be driven — holding each other accountable and to a high standard. Joining our team, you'll work alongside people who strive to be the best they can be, on complex projects across GC's data and business systems stack. Our technologies: We endeavour to build simple, reliable systems, and we believe in using the best technology for each task. Technologies we use across GoCardless include Python, Google Cloud Platform, dbt, Airflow, BigQuery, and others. You're not expected to have expertise in all of these — most of our team have picked up tools once they've started working with us. The Role We are looking for a talented Data Engineer to help
About us GoCardless, a Mollie company, is a global leader in bank payments. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday. We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific. For more information, please visit www.gocardless.com and follow us on LinkedIn @GoCardless. Mollie is the leading payments and financial services partner for business, rooted in Europe, with global reach. Data at GoCardless You'll sit in our Data and Business Systems group, working with technical and non-technical people across the whole company. You'll be part of a collaborative data engineering team, working closely with analytic engineers, analysts, and business stakeholders to deliver data solutions that scale with our rapidly growing business. We're a large team with an extensive remit, and we expect every member to work with initiative and be driven — holding each other accountable and to a high standard. Joining our team, you'll work alongside people who strive to be the best they can be, on complex projects across GC's data and business systems stack. Our technologies: We endeavour to build simple, reliable systems, and we believe in using the best technology for each task. Technologies we use across GoCardless include Python, Google Cloud Platform, dbt, Airflow, BigQuery, and others. You're not expected to have expertise in all of these — most of our team have picked up tools once they've started working with us. The Role We are looking for a talented Data Engineer to help
About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About AlphaSense: AlphaSense is an equal-opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals. All employees share in the responsibility for fulfilling AlphaSense’s commitment to equal employment opportunity. AlphaSense does not discriminate against any employee or applicant on the basis of race, color, sex (including pregnancy), national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, military or veteran status, disability, or any other non-merit factor. This policy applies to every aspect of employment at AlphaSense, including recruitment, hiring, training, advancement, and termination. In addition, it is the policy of AlphaSense to provide reasonable accommodation to qualified employees who have protected disabilities to the extent requi
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 We’re looking for a Data Scientist to join our drug pricing optimization team supporting a major reseller health plan client. This is a strong opportunity for a data scientist who brings technical depth, practical problem-solving, and curiosity, and who wants to grow in a squad-based environment with real business impact. In this role, you would help the team solve complex pricing and optimization problems, contribute to data science workflows used in production-oriented settings, and partner with technical and business stakeholders to turn analytical work into clear decisions. Over time, this role offers room to grow into broader squad leadership responsibilities through strong ownership, follow-through, and communication. What you’ll do: Contribute to the design, development, and improvement of data science and optimization solutions for drug pricing Analyze complex datasets to identify patterns, issues, and opportunities that improve pricing performance and decision quality Build, test, debug, and maintain code in Python and SQL to support analytics, modeling, and operational workflows Breaking down messy business and technical problems into actionable analyses and practical next steps Work within cloud-based and production-oriented environments, including GCP and team development tools such as VS Code Suppo
Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! We are looking for Data Engineering interns who are excited to help scale the systems and pipelines that power decision-making at Figma. As an intern on our data team, you will partner with engineers and analysts to design and build reliable datasets, ensure data quality, and make Figma's data more accessible across the company. This internship will be based out of our San Francisco or New York Hub. What you'll do at Figma: Build, test, and document data pipelines that bring product or business data into Figma’s data warehouse Help design foundational datasets that are trusted, well-documented, and easy to use Optimize pipelines for performance and scalability as Figma grows Partner with cross-functional teammates to understand data needs and deliver solutions Contribute to the tools and practices that make working with data at Figma easier With support from a manager and mentor, you’ll own a scoped project from problem definition through implementation, testing, documentation, and sharing the results. Some projects you could work on: Develop new ETL jobs to integrate product or business data into our warehouse Improve the performance and reliability of core pipelines Build reusable datasets that support experimentation, product and business analytics, or cross-functional stakeholders Document and simplify complex data workflows for broader use We'd love to hear from you if you have: Experience coding in Python or a similar language and writing SQL queries Experience building or working with dat
Opportunity Overview: Lead analytics and clinical configuration strategy for our auto-decisioning platform, driving end-to-end solutions from data gathering through scaled deployment. Partner cross-functionally to translate business needs into analytical frameworks, independently recommending actions that shape product and business outcomes. Own auto-decisioning strategy for new client implementations with minimal oversight, while ensuring explainable, governance-aligned analytics practices. Build and mentor a high-performing team, embedding best practices for scalable, reusable analytics solutions. Ideal for a strategic thinker who thrives at the intersection of hands-on execution and team leadership in a fast-paced, data-driven environment. What you’ll do: Provide thought leadership & strategic thinking to translate business problems into analytical and clinical configuration frameworks,and independently recommend actions and provide business insights Collaborate with cross-functional partners to understand their business needs, formulate and complete end-to-end analytic solutions that includes data gathering, analysis, ongoing scaled deliverables, and presentations Establish and maintain effective performance tracking; identify product and program improvement opportunities, form hypotheses, propose, design and implement tests to drive enhancement and optimization Foster a collaborative and innovative culture, set clear goals, mentor staff. Establish best practices and coach team members to develop and execute complex analytics initiatives with scalability and reusability in minds Develop, implement, and monitor day-to-day operations of analytics and clinical configuration team Execute analytics initiatives that directly impact our auto decisioning roadmap and business outcomes while working as part of a cross-functional team. Partner with Data Governance to ensure tractable and explainable analytics and responsible data Research, design, execute and optimize
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is seeking a Senior Director of Consumer Data Science to lead a multi-team organization that partners across Consumer, Product, Engineering, and the broader business. You will set the strategy and operating model for consumer data science, strengthen the systems and standards that make scientific outputs reliable, actionable, and scalable, and guide high-impact decisions through measurement, experimentation, causal inference, and ML. This leader will help define how Reddit measures and improves relevance across the consumer journey—from retrieval and ranking to feed, search, recommendations, and community discovery—and will shape the organizational capabilities required to advance these systems over the long term. Accordingly, the role requires the technical depth to evaluate architecture and analytical investments, guide state-of-the-art ML system improvements, and the leadership presence to align senior leaders around difficult tradeoffs. What you’ll do Partner with senior leaders across Consumer, Product, Engineering, and business functions to define company-level bets, priorities, and tradeoffs. Set the data science strategy for Reddit’s feed, recommendation, search, retrieval, and ranking systems, including objective design, candidate generation, ranking quality, relevance evaluation, experimentation, and long-term optimization. Establish the measurement and experimentation framework for relevance optimization, including offline evaluation, online experimentation, counterfactual analysis, guardrail met
Leidos is seeking a highly analytical and curious Data Analyst who is passionate about turning data into actionable business insights. The ideal candidate combines strong technical expertise with critical thinking and exceptional communication skills. This role requires someone who can work independently, uncover meaningful patterns in complex datasets, and communicate findings in a way that drives informed business decisions. *The Data Analyst will be a hybrid role, 50% onsite in the Fort Worth, TX office and 50% remote. The candidate for this role must be within commutable distance to the office location. Primary Responsibilities: Extract, clean, transform, and validate data from multiple sources, including relational databases. Write efficient SQL queries to retrieve, manipulate, and analyze large datasets. Develop Python-based data analysis workflows for data exploration, modeling, and reporting. Perform exploratory data analysis (EDA), including univariate, bivariate, and multivariate analysis. Apply statistical methods and predictive modeling techniques such as linear regression and other statistical evaluations. Utilize AI and machine learning tools to identify trends, generate insights, and improve analytical processes. Build and evaluate machine learning models, including: Regression Classification Clustering Decision Trees Supervised Learning Unsupervised Learning Investigate data anomalies and independently determine the root causes behind unexpected results. Identify the most relevant data elements, metrics, and business questions without requiring extensive direction. Translate complex analytical findings into clear, compelling presentations and recommen
Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: Join the Zynga Poker Analytics Team Zynga Poker is seeking a Principal Data Analyst to help drive decisions that impact millions of players worldwide. At Zynga, Principal is the next step above Senior; a great fit for analysts ready to take on broader ownership and scope. As part of our analytics team, you'll play a crucial role in shaping the future of our game through data-driven insights. Here's how you'll shape the player experience: Product Strategy: Analyze long and short-term trends to deliver insights that influence product direction Experimentation: Design, conduct, and analyze statistically sound experiments that drive measurable impact Business Intelligence: Maintain comprehensive dashboards and ETL pipelines to keep the organization informed on game performance Game Integrity: Enha
Location: Doha | Practice Area : Technology & Engineering | Type: Permanent Protect critical data. Strengthen controls. Reduce information risk. The Role Capco is looking for a Data Protection & DLP Consultant to help our clients protect sensitive and critical information across complex technology environments. This is an opportunity to work on complex data protection challenges within financial services, helping clients strengthen controls, reduce data leakage risks, and meet security, governance, and regulatory requirements. What You’ll Do Design and implement a comprehensive, multi‑layered data protection strategy incorporating data classification, data discovery, encryption controls, and DLP technologies. Design, implement, and enhance Data Loss Prevention policies, controls, processes, and technical solutions across enterprise environments. Identify and classify sensitive data, translating business and regulatory requirements into practical rules and controls. Monitor and assess alerts and incidents, supporting investigation, remediation, tuning, and continuous improvement. Work with security, data, risk, technology, and business teams to integrate DLP controls across endpoints, networks, cloud platforms, and applications. Maintain documentation, reporting, and governance processes associated with data protection and DLP operations. Support governance, reporting, control effectiveness assessments, and the development of sustainable data protection practices. What We’re Looking For Strong experience in Data Loss Prevention, information protection, data security, or related cybersecurity and data disciplines. Practical knowledge of DLP technologies, data classification, information protection, policy management, monitoring, and incident management. Experience implementing or managing DLP controls across endpoints, email, networks, cloud services, and enterprise applications. Strong understanding of data governance, security controls, risk management, priv
Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer Manager, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. Mentor and guide engineers, fostering knowledge sharing and best practices. What we are looking for? 8+ years of industry experience in data engineering. Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services (MS Azure, GCP, AWS), ML Modeling, Spark & Kafka. Data modelling and modern data platform design concepts Building and maintaining data platforms in Azure/AWS or GCP Experience working with business stakeholders either internally or externally Excellent communication skills to collaborate effectively within teams and with stakeholders.
Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Data Scientist II Role Overview Build and productionize enterprise-grade AI and Generative AI solutions for Mastercard. This role combines strong software engineering with model fine-tuning, Databricks-based ML engineering, AWS deployment, and end-to-end MLOps. Key Responsibilities Design, develop, test, and maintain scalable AI/ML applications, APIs, and reusable engineering components. Fine-tune and evaluate foundation models using techniques such as LoRA, QLoRA, PEFT, and supervised fine-tuning. Build RAG solutions, embeddings workflows, vector-search applications, and AI agents. Create end-to-end ML pipelines for data preparation, training, evaluation, deployment, monitoring, and retraining. Use Databricks, PySpark, MLflow, Unity Catalog, Workflows, Vector Search, and Model Serving for governed model development and operations. Implement CI/CD, automated testing, observability, model monitoring, and production support practices. Partner with data science, engineering, product, security, privacy, and governance teams to deliver reliable and responsible AI solutions. Required Skills & Experience 3–4 years of experience in AI/ML engineering, software engineering, data science, or a related field. Strong Python, SQL, object-or
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