Data Science Director Jobs

Education: Master or Bachelor’s degree in computer science, information systems management or related field. Solution and Architecture certifications such as TOGAF or other. Experiences: More than 12+ years of experience in information technology, with 8+ years spent in data architecture or technology solutions definitions and implementations. Extensive experience in banking and financial services domain Knowledge & Skills: Expertise in Data Architecture, Data Strategy and Roadmap for large and complex organization and systems and implemented large scale end-to-end Data Management & Analytics solutions Experience in transforming traditional Data Warehousing approaches to Big Data based approaches and proven track record of managing risks and data security Expertise with DW Dimensional modeling techniques, Star & Snowflake schemas, modeling slowly changing dimensions and role playing dimensions, dimensional hierarchies, and data classification Experiences in cloud native principals, designs and deployments. Extensive experience working with and enhancing Continuous Integration (CI) and Continuous Development (CD) environments Expertise in Data Quality, Data Profiling, Data Governance, Data Security, Metadata Management, and Data Archival Define workload migration strategies using appropriate tools Drive delivery in a matrixed environment working with various internal IT partners Demonstrated ability to work in a fast paced and changing environment with short deadlines, interruptions, and multiple tasks/projects occurring simultaneously Must be able to work independently and have skills in planning, strategy, estimation, scheduling, Strong problem solving, influencing, communication, and presentation skills, self-starter Experience with data processing frameworks and platforms (Informatica, Hadoop, Presto, Tez, Hive, Spark etc.) Hands-on experience with related/complementary open source software platforms and languages (e.g. Java, Linux, Python, GIT, Jenki

JOB TITLE Data Reliability Engineer A CAREER WITH CUBIST Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Ensure smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe Serve as a frontline owner for mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with investment professionals, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s REQUIRED Bachelor’s degree in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal skills. Commitment to the highest ethical standards About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Poin

Data Engineer Description - Key Roles Designs and establishes secure and performant data architectures, enhancements, updates, and programming changes for portions and subsystems of data pipelines, repositories or models for structured/unstructured data. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of data system or component; identifies and debugs, and creates solutions for issues with code and integration into data system architecture. Collaborates within a project team of other data engineers to develop reliable, cost effective and high-quality solutions for assigned data system, model, or component. Analyzes data inaccuracies, identifies opportunities and supports the development of automated solutions to enhance overall quality of the enterprise data. Identifies problematic areas and conducts research to determine the best course of action to correct the data; identifies, analyzes and interprets trends and patterns in complex datasets. Works cross-functionally with different departments to assess, define, and develop report deliverables. Represents the software data engineering team for all phases of larger and more-complex development projects. Provides guidance and mentoring to less experienced staff members. Education & Experience Recommended Four-year or Graduate Degree in Computer Science, Information Technology, Software Engineering, Statistics/ Mathematics, or any other related di

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. Sr. Data Cloud Engineer(s)(multiple positions) – Duties are using relational database systems, CI/CD pipeline, Kubernetes for application deployments, terraform IAC, Observability using Splunk, server-side GitHub REST API, & Snowflake, Spark, & Python to design, automate, implement & maintain data architecture patterns in AWS & GCP for data collection infrastructure & pipelines for multi-region cloud-based big data IaaS & PaaS solutions including performing requirements & document use technology analysis; coordinating data integration & ETL processes; supporting data security, integrity & cost controls; automating data processes utilizing Cloud Composer & develop SQL scripts for data modeling; performing end-to-end pipeline load performance testing; supporting technology upgrades through PostgreSQL & Cloud SQL cloud migrations; performing SQL & NoSQL database tuning & maintenance; providing guidance on data management & SQL optimization; & developing data warehousing management policies. Requires Bach degree in Comp Science, Comp Engineering, Information Technology (IT) or related field & 5 yrs exp in job duties as stated. Position is with Dun & Bradstreet in Jacksonville, FL. Inquire and send resume through Dun & Bradstreet’s job board at https://jobs.lever.co/dnb. Position is under Sr. Data Cloud Engineer for Jacksonville, FL. #LI-DNI

A Career with Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What You’ll Do We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . This role focuses on advancing the science and systems behind ML measurement, feature understanding, and causal inference at scale. The work spans areas such as production feature importance platforms, observational causal estimation in Pytorch, large-scale proxy metric development, and data-driven approaches to ML infrastructure efficiency. We're looking for an enthusiastic individual contributor to perform high-impact technical work across this space. This person will drive foundational innovations, own the end-to-end design of production ML systems, establish rigorous methodological standards, and partner cross-functionally to turn successful research into durable platform capabilities that raise the ceiling for the entire ML organization. What you’ll do: We are looking for an experienced and highly capable Data & Applied Scientist

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. Responsibilities: Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. Design and implement APIs to facilitate data interactions between internal services and external data sources. Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. Optimize backend services for performance, scalability, and security in a distributed computing environment. Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in full-stack development. Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). Experience building data-intensive applications that handle large-scale datasets. Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). Prior experience with web crawling and large-scale data processing is a

JOB TITLE Reference Data Engineer A Career with point72’s Cubist TEAM Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What you’ll do Develop, test, and maintain software applications using .NET Full Stack technologies. Write clean, scalable, and efficient code in Python for various applications. Collaborate with cross-functional teams to define, design, and ship new features. Implement and manage CI/CD pipelines and other DevOps practices to ensure smooth deployment and operation of software solutions. Participate in code reviews and contribute to a culture of continuous improvement. Troubleshoot and resolve software defects and issues in a timely manner. Stay up to date with emerging technologies and industry trends to enhance skills and knowledge. What’s REQUIRED We are looking for a motivated and skilled Software Engineer with experience in .NET Full Stack development, Python, and DevOps. You should also have: Bachelor’s or master’s degree in computer science, engineering, statistics or a related field. 3+ years of experience in .NET Full Stack development and Python programming. Basic understanding and practical experience with DevOps tools and methodologies. Strong problem-solving skills and attention to detail. Excellent communication skills and the ability to work collaboratively in a team environment. Eagerness to learn and adapt to new technologies and challenges. Commitment to the highest ethical standards. About point72 Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its inves

About Us: Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm’s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. Job Summary: Build systems for collection & transformation of complex data sets for use in production systems Collaborate with engineers on building & maintaining back-end services Implement data schema and data management improvements for scale and performance Provide insights into key performance indicators for the product and customer usage Serve as team's authority on data infrastructure, privacy controls and data security Collaborate with appropriate stakeholders to understand user requirements Support efforts for continuous improvement, metrics and test automation Maintain operations of live service as issues arise on a rotational, on-call basis Verify whether data architecture meets security and compliance requirements and expectations .Should be able to fast learn and quickly adapt at rapid pace. java/scala, SQL, Minimum Qualifications: Bachelor's degree in computer science, computer engineering or a related field, or equivalent Experience 6+ years of progressive experience demonstrating strong architecture, programming and engineering skills. Firm grasp of data structures, algorithms with fluency in programming languages like Java, Python, Scala. Strong SQL language and should be able to write complex queries. Strong Airflow like orchestration tools. Demonstrated ability to lead, partner, and collaborate cross functionally across many engineering organizations Experience with streaming technologies such as Apache Spark, Kafka, Flink. Backend experience including Apache Cassandra, MongoDB and relational databases such as Oracle, PostgreSQL AWS/GCP Solid hands on with 4+ years of experience. St

Senior Human Data Operations Partner, AI Team: Human Data Prolific Prolific is not just another player in the AI space – we are the architects of the human data infrastructure that's reshaping the landscape of AI development. In a world where foundational AI technologies are increasingly commoditized, it's the quality and diversity of human-generated data that truly differentiates products and models. The role As a Senior Human Data Operations Partner, you will play a pivotal role in ensuring the smooth execution of end-to-end operational processes that power Prolific's specialised participant pools. You’ll act as a key enabler for client-specific projects, working closely with delivery teams to align participant-related processes with strategic AI customer needs. You’ll also work to transform these processes and workflows into scalable solutions, partnering closely with our product and tech teams to do this. This role demands a hands-on approach to participant onboarding, verification, and quality management, as well as cross-functional collaboration to meet the demands of both internal stakeholders and external clients What you’ll be doing in the role Develop detailed project plans, workflows, and enablement materials to support efficient delivery. Maintain Prolific’s participant pools as high-quality, diverse, and optimised to meet customer demands. Implement and manage verification processes for domain experts and AI taskers, ensuring their skills and qualifications meet client-specific requirements. Continuously optimise participant onboarding and activation funnels to enhance retention and task performance. Monitor participant engagement and quality metrics, using insights to drive improvements. Contribute to upskilling programmes and certification processes for participants involved in complex AI tasks Work closely with product, data, science, and customer success teams to align operational priorities with strategic objec

A CAREER WITH POINT72’S DATA SOURCING TEAM: We are looking for a Market Data Operations Associate to join our Enterprise Data Sourcing Team to help manage day-to-day market data operations around data governance, entitlement management, and market data support. In this role, you will support our expanding data requirements and strategic business initiatives around firmwide market data. What you’ll do: Manage and monitor market data and service change notifications from exchanges and other key market data suppliers Identify any gaps in market data usage and coverage and provide proper licensing recommendations Administer and manage market data entitlements for market data feeds (e.g. TREP, BPIPE) and terminals (e.g. Bloomberg Terminals, FactSet Workstation, CapIQ) Help manage exchange audits to fulfil their requirements, including working with usage statistics via SERS / DACS / EMRS reports Help ensure the firm’s market data access and usage is compliant with licensing agreements Help manage the full lifecycle of market data exchange contracts and renewals, including tracking of user inventory and key commercial terms Help provide additional ad-hoc administrative support around the firm’s market data operations, including invoice reconciliation, internal reporting, etc. What’s required: Bachelor’s or Master’s degree in finance, economics, computer science, business, or related field (with a strong academic record). 4+ years of experience in market data management within a financial services or trading environment. Strong understanding of exchange data licensing, entitlements, and governance policies. Familiarity with market data platforms, feed technologies, and integration processes. Knowledge of global trading markets and regulatory requirements. Strong problem-solving skills with the ability to anticipate issues and propose solutions. Detail-oriented with the ability to track policy changes and ensure operational compliance. Proj

Datadog AI Research — Scholars Program with Carnegie Mellon University Datadog AI Research (DAIR) is partnering with Carnegie Mellon University to support a small number of PhD students working on open research problems grounded by ongoing efforts at Datadog/DAIR. You will frame a problem, run your own experiments, and write up what you find, with compute and data at a scale most academic labs cannot provide. You will collaborate with colleagues working on the same questions. The Lab And The Research: DAIR is an industrial research lab motivated by practical challenges in observability and software operation: detecting and diagnosing failures, understanding complex production environments, and helping engineers operate software more effectively. The lab focuses on creating specialized foundation models, post-training and evaluating AI agents, and building frontier-scale machine learning systems. By combining fundamental research with Datadog's large-scale, real-world data and infrastructure, the lab develops new AI capabilities and translates them into practical systems with meaningful impact. Internship projects are shaped with your DAIR mentor and your CMU faculty advisor. You do not need prior experience with observability, monitoring, or infrastructure. What You'll Do: Own a research project end to end: framing the question, running the experiments, writing it up Work directly with a DAIR mentor engaged in the same problem, and stay connected to your advisor and lab Publish, and use the work toward your dissertation See research reach production, when it works Who You Are: Currently enrolled in a PhD program at Carnegie Mellon in machine learning, computer science, statistics, or a related field Depth in at least one area relevant to the research above Comfort running real experiments — training models, working with GPUs, reading and reimplementing recent papers Evidence you can do research: conference or workshop papers, preprin

Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere. The Team Our AI research team sits at the heart of our mission to unlock new dimensions of biological understanding. You will leverage state-of-the-art AI to accelerate discovery and drive transformative insights in biology—developing novel AI models purpose-built for biological research, engineering robust systems that enable breakthrough science at unprecedented scale, and translating these advances into practical tools that empower researchers worldwide. Our approach is comprehensive and integrated, bringing together world-class AI model development, exceptional engineering talent, high-quality biological data, powerful computing infrastructure, and strategic partnerships. Success requires excellence across five interconnected pillars: training frontier AI models specifically for biology; building engineering systems that maximize research velocity and efficiency; executing a sophisticated data strategy that fuels AI development; operating a world-class AI compute platform; and creating impactful products that transform AI capabilities into accessible scientific tools. The Opportunity This role is part of the Data team, which focuses on owning the strategy, sourcing and implementation for data supporting AI research and development. Our goal is to maximize the speed, agility, and capability of biological AI research by connecting public data resources and Biohub's experimental platforms to AI systems. The data that trains biological frontier models comes in dozens of modalities—sequences, images, sp

Location : Come and join us in Hamburg, Berlin or Barcelona! Freenow by Lyft empowers smarter mobility decisions helping people to move freely and cities to thrive. We are looking for a Senior Data Analyst (m/f/d) to collaborate with our operational squads. In this role you will be able to become an expert in our business and data analysis systems and environment to allow you to champion data-driven decisions as part of the Data Operations team. Be ready to work in a multinational, diverse, highly motivated and collaborative team of passionate analysts who strive for excellence and like to have fun. Are you ready for your next ride? YOUR DAILY ADVENTURES WILL INCLUDE: Focus on analysing and presenting recommendations/process changes/new initiatives to management using insights derived from data. Use your technical skills such as actively engaging in configuration and programming in the data environment, querying data via SQL from the data lake, automating data processes, deep dive analysis in Python and adjusting ETL tasks. Bringing new insights and championing them using your analyses, dashboards, and good storytelling! We value ideas over hierarchy, and there's always a new path to follow if your idea is convincing and well-backed with data. Develop monitoring tools to measure performance and help the business achieve its objectives. Create queries to answer operational and business questions across our many operational teams to support decisions. Communicate results in a clear and impactful manner. TO BE SUCCESSFUL IN THIS ROLE: Educated to Degree Level or higher in an analytical discipline such as Engineering, Computer Science or Economics 5+ years of experience in an analytical role You have curiosity in your essence, which motivates you to answer WHY things happened, not only scratching the surface, but aiming for well-founded actionable results Curiosity about AI and its practical applications in analytics, experience using LLMs or AI-powere