Python And Sql Business Analytics Analyst in New York

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to car

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role NYT Wirecutter is looking for a Senior Manager, Revenue Analytics to power our business strategy. Your core mandate is to increase audience monetization across our primary businesses—Affiliate, Advertising, and E-commerce—ensuring we preserve long-term audience trust. As a player-coach role, you will lead a team of analysts and partner closely with Revenue, Product, and Marketing leads to establish KPIs, run conversion experiments, and build attribution frameworks that scale revenue. You will report to the Executive Director, Data Analytics. Responsibilities You will lead, mentor, and onboard a team of two direct reports, nurturing their career growth You will analyze affiliate revenue drivers (e.g., merchant commissions, EPC, conversion rates, and partner yield) across all content touch points. You will be the analytics lead for the newly launched Wirecutter Store, reporting on unit economics, merchandise performance, cart funnel analytics, order value (AOV), and customer acquisition/repeat purchase metrics You will partner with Ad Ops and Advertising teams to track ad yield (RPM, eCPM), fill rates, and ad unit viewability, balancing display and custom content revenue against user experience and page speed You will evaluate trade-offs between affiliate links, ad placements, and Wirecutter Store product placements on site, creating a holistic monetization framework to maximize total revenue per user. You will lead recur

About DataCamp DataCamp's mission is to empower everyone with the data and AI skills essential for 21st-century success. By providing practical, engaging learning experiences, DataCamp equips learners and organizations of all sizes to harness the power of data and AI. As a trusted partner to over 20 million learners and 6,000+ companies , including 80% of the Fortune 1000, DataCamp is leading the charge in addressing the critical data and AI skills shortage. About the role + Responsibilities The Learning Solutions Architect is a customer-facing technical trainer who helps organizations build data and AI capabilities with DataCamp. You’ll deliver engaging live training (virtual and onsite) and create tailored learning materials on the DataCamp platform—think custom courses, projects, certifications and assessments that map to each customer’s roles, tools, and outcomes. You’ll partner with Customer Success, Sales, Product and Content to scope blended learning paths, teach high-impact sessions, and publish reusable, high-quality content that accelerates adoption and measurable skill uplift for some of our most high-value customers. Qualifications Loves to teach. Comfortable spending multiple hours weekly in front of a virtual or onsite classroom. 2+ years in technical training, data science/analytics education, solutions engineering, or similar instructor roles. Broad technical range across AI, Python/SQL/R and Power BI/Tableau; familiarity with Databricks/Snowflake is a plus. Learns new tools quickly; enjoys tailoring content to different personas (analyst, engineer, business user, exec). Strong communicator who can simplify complex topics for technical and non-technical audiences. Detail-oriented and process-driven; delivers sessions and materials with substance. Flexible schedule to support time zones (this is not a 9 to 5); occasional travel for onsite delivery. Some of your key metrics will be: Customer satisfaction: survey, engagement, repeat bookings Profe

As a Finance Systems Analyst, you will play a key role in modernizing Datadog's finance organization through process automation, data analytics, and financial systems optimization. Working within the Finance Systems team, you will partner closely with Accounting, FP&A, Tax, and other finance stakeholders to improve the efficiency, accuracy, and scalability of financial processes and reporting. You will leverage technologies such as AI tools, SQL, Python, Tableau, and financial systems to analyze data, automate workflows, and deliver actionable insights. This role offers an opportunity to help shape how emerging technologies, including AI, transform finance operations while contributing to strategic decision-making across the business. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Partner with Accounting, FP&A, Tax, and other Finance stakeholders to gather requirements and translate business needs into scalable reporting and analytics solutions. Collaborate with cross-functional teams including IT, Business Systems, Sales Systems, and Analytics to drive data and automation initiatives. Build and maintain dashboards and reporting tools that monitor financial and operational performance and support evolving business priorities. Automate recurring finance processes and enhance data workflows using AI tools, data visualization platforms, and custom solutions. Support financial system implementations and upgrades through data migration, mapping, reporting integration, testing, and validation activities. Deliver analytical insights and maintain documentation that enables self-service reporting and informed decision-making across Finance. Who You Are: Have 1-5 years of experience in data analytics, financial systems, finance operations, or a rel

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role New York Times Wirecutter team is looking for a Senior Manager, Audience & Product Analytics to power our growth strategy. Your core mandate will be to build an understanding of our audience— who they are, how they engage with content and product features, and what brings them back. You will lead a team of analysts responsible for understanding audience trends, driving product improvement, and optimizing user engagement. You will provide leadership and data-driven insights, working with audience, product, and engineering leads to establish goals, design experiments, and uncover new opportunities. You will report to the Executive Director of Data Analytics and Insights, Wirecutter. This opportunity is flexible to in office or remote work. Responsibilities You will manage a team of three direct reports—promoting a culture of curiosity and excellence while setting clear deliverables, supporting career growth, and ensuring high-quality analytics output You will analyze audience growth, traffic drivers, customer journey touch points, and user engagement trends to inform strategic decision-making. You will partner with functional leads (Product, Design, Engineering, Editorial) to set strategy, define goals, and build the audience and product analytics roadmap. You will lead the design, execution, and post-analysis of product experiments (A/B testing). Provide expertise on primary metrics, trade-offs between competing goal

Datadog's Finance team collaborates with teams across the organization, providing commercial, operational and analytical support to ensure that Datadog's business continues to scale rapidly and efficiently. The Financial Planning & Analysis (FP&A) team analyzes company financial data (revenue, customers, headcount, expenses, etc.) in order to support the business’ growth and success. As an analyst supporting the team, you will play a key role in delivering insights through the management of essential data infrastructure, including our financial planning tool, Pigment. Your role will be highly cross-functional, leveraging systems and data to unlock analytical capabilities for both FP&A and business leaders. Your role is critical in synthesizing information from across the organization to foster operational alignment and support informed strategic decisions. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the team’s forecasting and reporting software, Pigment, supporting data-driven insights through the development of dashboards and KPIs, both for standard FP&A reports and ad hoc projects Work cross-functionally with FP&A leaders to improve existing datasets and models Ensure data and system best practices in processes across the organization, including during planning and reporting cycles Represent FP&A in the data & analytics community, collaborating with analytics partners across the organization to democratize data and share insights Work on strategic projects and initiatives for senior management, assessing various business opportunities and proposing solutions Support Datadog’s data-based decision making and continued efficient growth Who You Are: 2+ years of professional experience in FP&A, Data Analy

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a member of our Analytics & Data Insights team, you'll tackle the kind of problems that don't have textbook answers yet, launch products that didn't exist a year ago, and help enterprises understand what foundational AI actually means for their bottom line. As a Data Engineer, you will: Work directly on new customer experiences built on one of the most advanced AI systems in the world Collaborate daily with researchers and engineers who are some of the best in the world at what they do Run implementations end-to-end and see initiatives through to real outcomes Partner across research, marketing, sales, and finance to help define how Cohere grows, with your recommendations feeding directly into products and strategy You may be a good fit if you have: 5+ years of experience working on production-grade data processing systems Strong command of Python and SQL Experience with distributed data processing frameworks such as Apache Beam, Spark, or

About Us: AI needs a new infrastructure layer. We're building it at Modal. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Lovable , Ramp , Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September. Our team includes creators of popular open-source projects (e.g., Seaborn , Luig i ), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. About Modal Data: We’re growing our Data team and are looking for our first few key hires to build self-serve data tools and drive business strategy in the right direction. The mission of the Modal Data team is to make it easy to track company goals, make evidence-backed decisions, and prioritize the right work. We do this via: Self-serve AI analytics tools (Hex, Snowflake) Embedding with teams as a “data adviser”, providing strategic analysis and consulting What You'll Do: Contribute to building the most modern analytics stack in Data today to support AI-driven self-serve analysis, key metrics tracking, and external customer reporting Influence work on new products like LLM Inference Endpoints through product analytics tracking Identify millions of dollars of cost savings and optimization across our tools and financial operations Write data pipelines that power the operatio

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

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 II, 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 c

Use Your Power for Purpose Global Commercial Analytics (GCA) harnesses the power of data to drive robust analytical insights that inform some of Pfizer's most critical business questions. With colleagues across the globe, GCA's rigorous analytical expertise is depended on as the compass and decision support for the enterprise. Our dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including data science, market research, digital analytics, finance, and consulting. As a team, we partner to turn data into meaningful insights that will have a direct impact on patients' lives and the future of Pfizer as a data-driven organization. The Data Science Manager is accountable for delivering data science support across the commercial business. As a strategic partner to US Commercial teams, this person will develop and implement models and data science-derived insights that influence brands’ strategic priorities. These responsibilities will include driving the execution and interpretation AI/ML models, framing problems, and shaping solutions. This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. The successful candidate will join GCA colleagues worldwide that are constantly supporting business transformation through their proactive thought leadership, innovative analytical capabilities, and their ability to communicate highly complex and dynamic information in new and creative ways. What You Will Achieve Commercial Data Science and Insights Provide data science and insights to US Commercial teams to drive brand tactic decisions Assist to frame, investigate, and translate complex data-informed models, and answer key business questions related to the identification and evaluation of brand strategies a

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Data Platform builds infrastructure and tools that enable Ramp to realize business value from data. We partner closely with stakeholder teams to build this infrastructure and the applications on top of it. This role is particularly focused on building platforms that support the data science development lifecycle. You’ll partner with applied scientists, AI engineers, Risk engineers, and other ML developers on building infrastructure and tools that enable and accelerate the development of machine learning models. What You’ll Do Build and integrate the components of Ramp's Analytics Platform and Machine Learning Platform. Build tools that improve the agility and data experience of Ramp's Applied Scientists, AI Engineers, and Risk Engineers. Collaborate with stakeholder teams on building and productionizing machine learning applications. Build reliable, scalable, maintainable, and cost-efficient systems across the stack. What You Need Experience with workflow orchestrators like Airflow, Dagster, or Prefect. Experience building infrast

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who thrives at the intersection of data, AI, and complex enterprise architecture. In this role you will work directly with the sales team and channel partners to understand the data challenges of our customers, strategize on how to navigate winning sales cycles, deliver compelling data-driven demonstrations, and support enterprise Proof of Concepts that showcase measurable business outcomes. As a Snowflake Solution Engineer you must share our passion for transforming how organizations use data — from raw ingestion to real-time analytics to AI-powered applications. You thrive in a dynamic environment, are equally comfortable whiteboarding a medallion architecture with a data engineering team and presenting data ROI to a C-suite, and you bring deep opinions about what good data platform design looks like. IN THIS ROLE YOU WILL GET TO: Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward Build and deliver tailored demos and proof of concepts across Snowfla

About the Team DoorDash’s mission is to grow and empower local economies. By building intelligent, last-mile delivery technology for local cities, DoorDash connects people with the local businesses they care about — helping grow businesses and the communities that support those businesses. The Marketing Technology team is responsible for delivering best-in-class tools, data, and processes so teams at DoorDash can effectively acquire new customers, drive retention, and grow new business lines across all our audiences. Our mission is to enable teams to deliver personalized, engaging, and relevant content across all our owned and paid channels. We partner closely with Product, Engineering, Data Science, and Analytics teams to translate Marketing’s technology needs into measurable business outcomes for our Growth and Performance Marketing teams. About the Role We're looking for a Senior Associate, AI Solutions Architect to help build and scale AI-powered tools across DoorDash's Marketing teams. You'll work alongside our existing Marketing Technology AI Solutions Architects to identify opportunities where AI can solve real marketing problems, then build, test, and iterate on the solutions that make it happen. This role is grounded in hands-on building: you'll spend your time prototyping, coding, and shipping tools rather than pitching strategy from the sidelines. This is a great opportunity to grow your technical and strategic skills at the intersection of marketing and AI. You'll get mentorship from a team of builders and exposure to the full lifecycle of AI development from prototype to deployment. This role will report to the Senior Manager, Marketing Technology within the Growth Marketing organization. You're excited about this opportunity because you will… Build and deploy AI-powered tools and automations, such as automated reporting, QA frameworks, and workflow optimizations. Develop MVPs and proof-of-concepts, then iterate based on user feedback within a defined w

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Research Engineer in our Safety team, you will play a key role in helping develop safer, more secure, and more reliable models. Your primary focus will be on building tools to enable easy data synthesis, analysis, and management, for complex combinations of real and synthetic data that is used in both model training and evaluation. You will own the cohesive vision of these tooling repositories. You will work closely with a team of research scientists and engineers to create tooling that enables tighter experimentation cycles, better data coverage of the real world, and more scientific rigour. You will have a lot of autonomy and need to be opinionated about what areas of the codebase need elegance and standards, and where that would be overengineering. You will be given high level experimental problems that need to be solved with efficient pipelines, and design and implement the solutions. Your data analysis will collaboratively feed into modelling decisions and experimentation. This role combines expertise in software engineering, statistics, and data science. If any of these topics sound interesting t