Data Science Manager Jobs

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role The ADM Support team handles all client inquiries related to Addepar's Alternatives Data Management (ADM) solution post-implementation. ADM Support Analysts play a critical role in supporting some of the world's most sophisticated investors, answering questions and resolving issues related to their alternative investment data on the Addepar platform. They ensure clients get the most value out of each interaction by providing accurate, timely guidance across the full scope of ADM functionality. Our ideal candidate is tenacious about tackling problems, can skillfully coordinate with internal teams, and enjoys working directly with clients in the alternative investments space. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Identify, respond to, and resolve issues and questions raised by ADM clients, providing timely and accurate support. Work in complex alternative investment data sets to identify and resolve data and calculation discrepancies. Evaluate the criticality of client issues and collaborate with other internal ADM teams (Collections, Operations) to drive resolution. Conduct root-cause an

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role The Portfolio Services team is at the core processing Addepar’s client data. We play a pivotal role in enabling data to flow across our data platforms into our client’s instances. Working at the critical intersection of application, analyst, and operations teams, we promote developer velocity and robust process automation. Working with a healthy mix of new technologies and existing core applications, the team thrives on solving complex challenges to deliver high-impact solutions. If you're passionate about creating true engineering leverage, this is the team for you. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Work with teams across the organisation to: Develop resilient distributed services and high quality tooling to support product operations and engineering Investigate and debug complex issues that span across teams and applications Drive software delivery and improve the engineering processes we use to develop and release software Who You Are Comfortable working independently, with a bias for action Thrives in ambiguous spaces where there isn’t a clear solution Enjoys digging into new pr

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role The Platform Services team is at the core of accelerating Addepar’s platform scalability, elasticity, and global expansion. We play a pivotal role in driving innovation and standards for building distributed services and on-demand environments to meet the rapid scale of Addepar’s growth. Working at the critical intersection of application, infrastructure, and operations teams, we promote developer velocity and robust process automation. Working with a healthy mix of new technologies and existing core applications, the team thrives on solving complex challenges to deliver high-impact solutions. If you're passionate about creating true engineering leverage, this is the team for you. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position. What You’ll Do Work with teams across the organisation to: Develop resilient distributed services and high quality tooling to support product operations and engineering Investigate and debug complex issues that span across teams and applications Drive software delivery and improve the engineering processes we use to develop and release software Who You Are Comfortable working independent

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Finance vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of financial software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Finance industry, decide what financial tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Finance industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Finance workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real financial work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Finance AI roadmap & data strategy: Set product direction for the Finance agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Finance industry (including investment banking, private equity, public markets, corporate finance, FP&A, etc), driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Finance agentic capabilities fall short and shape new product lines and competit

About Prophecy The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how the world’s top enterprises turn data chaos into reliable insights. We introduce the AI-native data lifecycle (generate, refine, deploy) where our industry leading AI agents and humans work hand-in-hand in visual and document interfaces to analyze, transform and prepare data, to ship trusted insights at enterprise scale. Don’t miss the rocket ship—join Prophecy and build the next data revolution. Position Summary This is a high-impact opportunity to be a senior DevOps engineer in a fast-growing startup, based in Prophecy’s India engineering center. You will own and evolve the foundations that keep our engineering org fast, secure, and cost-efficient at scale — spanning cloud cost management, security DevOps, and CI/CD and engineering operations. You will work with a team of dynamic engineers who take pride in solving complex problems, and you will have the autonomy to set direction in your areas of ownership. The Impact You Will Have Cloud cost (FinOps) Own and evolve our cloud cost optimization program across AWS, Azure, GCP, Databricks, Snowflake and Bigquery building on the programmatic monitoring and controls Analyze billing, asset-inventory, and utilization data across departments to identify wasteful spend and provide actionable insights to optimize it. Develop and maintain cost optimization strategies, roadmaps, and forecasting models Partner with engineering teams to design cost-efficient architectures without compromising scalability or reliability. Build and maintain automation for infrastructure provisioning, scaling, and cost control. Security DevOps Partner with engineering and security to drive our security-hardening program across workstreams such as identity & access governance, secrets & credential lifecycle, cloud access, and CI/CD hardening. Implement and automate guardrails: secrets management, least-privilege access, cr

About Prophecy The leader in AI-native data preparation and analysis, Prophecy is revolutionizing how the world's top enterprises turn data chaos into reliable insights. We introduce the AI-native data lifecycle (generate, refine, deploy) where our industry leading AI agents and humans work hand-in-hand in visual and document interfaces to analyze, transform and prepare data, to ship trusted insights at enterprise scale. To learn more, visit us on LinkedIn. Position Summary This is an exceptional opportunity to be a technical leader on the team that powers the heart of Prophecy: the Runtime, our orchestration and execution service. Every data workflow , whether generated by our AI data agents or built by a human in the visual editor , is planned, scheduled, and run at enterprise scale by Runtime, directly against the customer's own platform (Databricks, Snowflake, BigQuery, and more). When a business user asks an agent a question and sees trusted results seconds later, Runtime is what made it happen. As a Staff Engineer, you will set the technical direction for this service: the distributed execution engine, the task coordinator, the multi-engine connectors, and the fast interactive previews that make the AI-native experience feel instant. You will own hard, ambiguous, high-leverage problems end-to-end , from architecture to production reliability , and raise the bar for the engineers around you. We're seeking A players to work with A players. We're a high-growth company on a once-in-a-lifetime journey to revolutionize the way data is prepared and analyzed. Be a part of it. The impact you will have Own the engine behind the product. Architect and evolve the runtime service that turns agent- and human-authored data workflows into high-performance jobs that run reliably in production and interactively during authoring. This is deep-tech at the center of the platform. Make it fast and make it scale. Design the distributed execution and task-coordination layer , schedul

Role: DataOps Solution Architect — Azure Data Platform (Fabric & Databricks) Owns end-to-end architecture of the Azure data platform (Fabric, Databricks, Azure services) and sets the governance, security, and DataOps standards engineering teams implement. Design authority and primary architecture advisor to the client, not the day-to-day builder. Experience Required 8-10+ years overall in data engineering / cloud architecture, including 3+ years as a Solution Architect or in a comparable design-authority role. Microsoft Fabric: 2+ years hands-on. Azure Databricks: 4+ years hands-on. Proven track record designing and delivering enterprise-scale Azure data platforms end-to-end. Azure is mandatory ; experience across multiple client engagements or a consulting/SI background is a plus. Core Technical Expertise Azure Platform Fabric & Databricks architecture. ADF. ADLS. Entra ID. Key Vault. Monitor/Log Analytics. Microsoft Fabric Workspace & environment strategy. Lakehouse/Warehouse. OneLake. Pipelines/Notebooks. REST APIs/CLI. Governance. Azure Databricks Workspace strategy. Unity Catalog. RBAC. Jobs/Workflows. Delta Lake. Asset Bundles. ML platform integration. DevOps & IaC Azure DevOps/GitHub CI/CD. Terraform & Bicep. Branching/release strategy. Reusable IaC modules. Security & Networking Entra ID. RBAC architecture. Private Endpoints/DNS. Key Vault integration. DataOps Standards CI/CD & test gates for pipelines. Data-quality frameworks. Observability/alerting architecture. SLAs/SLOs. Incident-management practices. FinOps guardrails. Key Responsibilities Own end-to-end architecture; translate requirements into scalable, secure, cost-effective designs. Design enterprise-scale Fabric/Databricks architecture including workspace, networking, security, and governance. Set standards for CI/CD, IaC, DataOps, and environment management; ensure enterprise security and regulatory compliance. Evaluate technology options; identify architectural risks a

Role Description We are looking for a data-driven, systems-thinking Sales Operations Manager to own the operating infrastructure that powers our go-to-market engine. In this highly visible Individual Contributor role, you will serve as the backbone of a regional Sales organization and translate go-to-market strategy into an executable operating model. You will act as the primary regional business partner for sales executives , supporting all routes to market within the region. You will own or coordinate supporting sales planning, territory and quota execution, forecast interpretation, operational improvements, and translation of strategic priorities into clear execution plans . You’ll drive process clarity, pipeline health, forecasting hygiene, and cross-functional governance, using AI and automation-enabled workflows to reduce manual reporting effort while maintaining strong human judgment over business recommendations. Your top priority each day will be to ensure excellence in execution and reporting on our regional goals. Responsibilities Own the operating cadence, including territory management, account segmentation, forecasting governance, pipeline inspection, business reviews, and performance visibility, delivering executive-ready insights that drive forecast accuracy, balanced sales coverage, and operational excellence .Partner with regional Sales leaders across all routes to market to improve forecast accuracy, pipeline health, sales coverage, deal quality, and operational execution. Work in close partnership with the Chief Business Officer’s organization and the GTM Strategy & Programs team to connect regional Sales Operations to company-wide priorities, provide timely inputs for executive reporting, and ensure consistency across regional and corporate operating cadences. Lead end-to-end coverage design, including segmentation, book cutting, territory planning, account assignment, capacity planning, and quota allocation in partnership with

WE'RE HIRING Senior SQL Data Engineer Azure & Snowflake Remote (WFH) Immediate Joiners only Location: Remote Employment Type: Full-Time Immediate Joiners Preferred Salary: Up to 8 LPA (PF Included) Experience: 4+ Years We are looking for a highly skilled Senior SQL Developer with strong experience in Microsoft Azure and Snowflake to design, develop and optimize enterprise data solutions. Must have 4+ years as a SQL Developer, Data Engineer, or Data Warehouse Developer, The successful candidate will have excellent SQL development skills, a strong understanding of data warehousing and data modelling, and hands-on experience building cloud-based data pipelines and analytical platforms. The role involves working closely with data architects, engineers, analysts and business stakeholders to deliver reliable, scalable and high-performing data solutions. Key Responsibilities -Design, develop and maintain complex SQL queries, stored procedures, views, functions and database objects. -Must have 4+ years as a SQL Developer, Data Engineer, or Data Warehouse Developer -Build and optimise data transformation processes for large-scale datasets. Develop data pipelines using Azure Data Factory, Azure Synapse Analytics and related Azure services. -Design and implement data solutions within Snowflake. -Develop Snowflake tables, views, stored procedures, streams, tasks, stages and file formats. -Create and maintain ETL and ELT workflows across Azure, Snowflake and source systems. -Analyse and improve the performance of SQL queries, data pipelines and warehouse workloads. Design dimensional models, including star and snowflake schemas, fact -tables and dimension tables. Implement data quality checks, validation rules, reconciliation processes and error-handling frameworks. -Support data migration and modernisation programmes from on-premises platforms to Azure and Snowflake. -Develop incremental loading, Change Data Capture and Slowly Changing Dimension solutions. -Troubleshoot da

About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About the Delivery Engineer Team As a member of the Delivery Engineer team, you will own the post-sales onboarding and data health for customers. Your goal will be to drive data trust, help embed Mixpanel into our customers’ data stack, and deliver on emerging AI integrations — delivering on the full value of Mixpanel as a self-serve analytics platform. You will work and consult with GTM team members and a diverse array of customers to successfully roll out product analytics to their organization and execute on technical projects and services that delight our customers. About the Role As a Delivery Engineer III, you will be on the front lines with our clients as they integrate Mixpanel into their core product development processes. You will lay the foundation for customers to adopt product analytics and get value from Mixpanel by delivering a world-class, on-time, and value-oriented onboarding experience. With your comprehensive project management knowledge, consultative approach, expertise in the analytics space, and technical knowledge of the modern data stack, you will lead our clients' first experience with Mixpanel as they incorporate product analytics into their data ecosystem as a foundational element. With your deep technical breadth and expertise in the analytics space, you’ll be the expert consultant on all things data and ecosystem. As Mixpanel and our customers continue to iterate on agentic integrations, you’ll own ensuring customers are able to build, assemble context, and integrate AI workflows with Mixpanel. Responsibilities Own onboarding and data health for our strategic and high-value

Site Lead - Future Projects will oversee Data Centre projects from start to finish, ensure pre-construction site preparedness, coordinating cross-functional teams, ensuring regulatory compliance, managing schedules and budgets, and maintaining quality standards. Responsibilities include identifying risks, updating stakeholders, and providing leadership and mentorship to project teams. Source: Adani Group | Job ID: 51586