Data Entry Specialist in New York

The Dashboards product is Datadog's unified single-pane-of-glass for metrics, logs, and traces—a comprehensive treasure trove of observability data. We are transforming Dashboards into an AI-native control surface and the central hub where every team moves seamlessly from question to insight to action – providing a guided experience that feels like having an expert SRE at your side and ensuring the entry point is never an empty canvas. We're hiring a Staff Applied Scientist to define and guarantee the quality of this AI system at scale. "Good" isn't one number — it spans answer quality, tool-selection accuracy (critical given the growing catalog of data sources and visualizations), retrieval relevance, latency, token cost, and end-to-end agent success. The space is full of open questions. How do you evaluate an agent end-to-end when the trajectory is non-deterministic? How do you score tool selection when a user’s query can result in the agent making decisions against dozens of visualizations and data sources – both of which are growing month over month? How do you build a measurement system that catches regressions across all widget types and data sources (e.g., enforcing correct grouping, sorting, and time overrides), and is easy to use and extend by dozens of teams? If those are the problems you want to spend your time on, come build this with us. 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 evaluation strategy for Dashboards, as well as sister teams within our organization. Define the metrics — offline and online, quality and cost, single-turn and multi-turn — that the team and the broader organization optimize against. Build the eval datasets, golden traces, and regression harnesses that catch quality changes before they hit customers, an

Sales Development is the front line of VTS’s growth engine. As an SDR, you’re not just booking meetings, you’re shaping our future. You’ll help identify and engage the next wave of customers who will use VTS to transform how commercial real estate operates. With the support of powerful data-driven workflows and AI tools, you’ll generate pipeline at scale, test new go-to-market strategies, and provide critical insights back to the sales and marketing teams. Simply put, when our SDR team thrives, the entire company grows faster. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office four days a week. ** What Makes This Job Awesome? This isn’t your typical entry-level sales role. At VTS, you’ll be joining a high-impact, AI-augmented sales team that’s rethinking how modern prospecting is done. You’ll: Be quickly trained in world-class SaaS sales techniques and real estate fluency. Use cutting-edge tools to automate busywork so you can focus on learning, experimenting, and connecting with decision-makers at some of the most influential CRE firms on the planet. Collaborate closely with AE mentors, marketing partners, and senior leadership to contribute directly to pipeline growth. See a clear path for promotion to closing roles and beyond. Our top AEs and leaders started in this seat. Be part of a scaling team where every win matters and every voice is heard. Form relationships with senior decision makers, asset managers and brokers at the top commercial real estate firms across the country. What Makes You a Great Fit? You’re not just looking for a job, you’re looking to launch a career in tech sales with real momentum. You could be a great fit if: You’re curious, coachable, and ready to dive headfirst into a fast-paced, goal-driven environment. You embrace new tools and technologies to work smarter and faster. You bring 1+ years of professional or internship experience. Bonus if it’s in CRE, SaaS, or sales but your

As we continue to revolutionize the commercial real estate industry, we're hiring an Associate Implementation Manager to join our team. This is an entry-level role built for someone ready to take things on and grow fast. You'll be embedded in a fast-moving implementation org, supporting clients and internal teams through onboarding, approval, and early adoption. You'll work cross-functionally to ensure a seamless experience from pre-sale through ongoing support, and you'll do it with an AI-first mindset , leaning on modern tools to work smarter, not harder. ** Please note that this opportunity is located in New York, NY, and requires this hire to work from our office four days a week. ** What you'll do : Drive Efficiency with AI - Approach every task with an AI-first mindset. Look for opportunities to leverage AI & Automation Tools to automate data collection, streamline workflows, and reduce manual lift. Project Execution Partnership - Partner on projects to plan, schedule, and manage project timelines from kickoff through portfolio go-live. Facilitate recurring project management meetings, build bespoke implementation plans tailored to client goals, and ensure each project lands on time, within scope, and against the right outcomes. Handle Varied Scope - Move between data onboarding, client-specific implementation plans, and internal projects without losing momentum. You'll juggle multiple priorities and know when to ask for help versus push through. Cross-Functional Collaboration - Work closely with Sales, Solutions, Customer Success, and Support to ensure a consistent client experience from pre-sale through ongoing support. Develop Toward Client Mastery - Actively participate in internal team strategy and project management meetings to hone “VTS Best Practices” toward managing client expectations and milestones, with a clear path to owning your own accounts. What makes you a great fit? AI Forward - You've used LLM & or automation tools like n8n, Cu

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company. What you’ll do As a Data Analyst II (DA), you will play a central role in enhancing the operational tracking and reporting capabilities of different business teams across Brex. You will work closely with Data Scientists, Data Engineers, and partner teams to drive meaningful insights for the business through visualizations, self-service tools, and ad-hoc analyses. This is a high-impact role in a fast-paced fintech environment where your work will directly influence strategic decisions. Where you’ll work This role will be based in our New York office. We are a hybrid environment that combines the energy and connections of being in

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. We’re looking for a Data Engineer II to help us build the next generation of products which will go beyond just ID and enable our members to leverage the power of a networked digital identity. As a Data Engineer at CLEAR, you will participate in the design, implementation, testing, and deployment of applications to build and enhance our platform- one that interconnects dozens of attributes and qualifications while keeping member privacy and security at the core. A brief highlight of our tech stack: SQL / Python / Looker / Snowflake / dbt What you'll do: Build a scalable data system in which Analysts and Engineers can self-service changes in an automated, tested, secure, and high-quality manner Build processes supporting data transformation, data structures, metadata, dependency and workload management Develop and maintain data pipelines to collect, clean, and transform data (owning end to end data product from ingestion to visualization) Develop and implement data analytics models Partner with product and other stakeholders to uncover requirements, to innovate, and to solve complex problems Have a strong sense of ownership, responsible for architectural decision-making and striving for continuous improvement in technology and processes at CLEAR What you're great at: 4+ years of data engineering experience Working with cloud-based application development, and be fluent in at least a few of: Cloud services providers like AWS Data pipeline orchestration tools like Airflow, Dagster, Luigi, etc Big data tools like Spark, Ka

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

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. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

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. We are the Data team within Plaid’s Fraud organization. We build the machine learning systems that power Plaid’s fraud detection products, leveraging Plaid’s network data to help identify and prevent fraud before it happens. Our team owns the end-to-end ML lifecycle, from feature pipelines and model training to production serving and monitoring, ensuring our systems are reliable, scalable, and built to support hundreds of customers and data partners. As a Data Scientist on the Fraud Data team, you will analyze customer and network traffic to understand how Plaid Protect performs across a range of use cases and customer segments. You’ll build dashboards and metrics that provide a clear, shared view of product performance, run backtests to evaluate performance and identify high-impact rules and model strategies, and generate insights that support customer growth and expansion. You’ll also design scalable data models and schemas to enable reliable analysis and reporting, while partnering closely with Product and Engineering to design and analyze experiments for new customer-facing features. Responsibilities: Work at the intersection of product analytics, machine learning, and fraud a

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

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

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. The Data Journalism team is looking for an experienced journalist with editing, management and data analysis skills to serve as an assistant editor. You'll help to run a group of data journalists who collaborate across the newsroom. You'll also advise on analyses conducted elsewhere in the newsroom. You should be obsessed with detail and rigor, display a knack for lifting stories to the next level and care deeply about developing your colleagues' talents. Collaboration is at the heart of this role; the Data Journalism team works with virtually every other desk in the newsroom. We'll expect you to deftly navigate these partnerships, which require crisp communication, a problem-solving attitude and a dash of diplomacy. This is an in-office position and includes regular attendance in the office four days a week. We have a preference for candidates who will work in New York City, with a secondary preference for Washington, DC. Important application requirement: Please submit a cover letter that describes your qualifications in the context of three stories (or projects) you helped to shape. For each, please provide a link to the work and describe your contributions in one to three paragraphs. Your cover letter should not exceed four pages in total. Within that limit, you are also welcome to provide a more traditional (but brief) description of your career and talents. Responsibilities: Help to lead the Data Journalism team Directly supervise seve

About Us: YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments. Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence. We operate globally with offices in the US, APAC, and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery. What It’s Like to Work at YipitData: YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals. From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers. Why Top Talent Chooses YipitData: Ownership That Matters : You’ll lead high-impact projects with real business outcomes Rapid Growth : We compress years of learning into months Merit Over Titles : Trust and responsibility are earned through execution, not tenure Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention If your ambition is matched by your work ethic—and you're hungry for a place where growth, impact, and ownership are the norm—YipitData might be the opportunity you’ve been waiting for. About Our Private Investor Business: YipitData has an opportunity to revolutionize the private investor market by providing something that has neve

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

At Datadog, we’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Observability Data Platform (ODP) is the backbone of everything Datadog delivers – powering how data is ingested, stored, routed, and surfaced across every product at planet scale. As a Senior Product Manager for ODP, you will work with world-class engineers and cross-functional partners to shape how the platform is deployed, controlled, and operated. You will define product direction across the control plane and data layer, translate complex infrastructure trade-offs into clear roadmap decisions, and help customers get the most from their observability investment – regardless of architecture, topology, or scale. 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 Will Do: Develop a deep understanding of the Observability Data Platform customers – platform engineers, SREs, and product managers that own the product verticals – their infrastructure challenges, deployment topologies, and cost-to-serve trade-offs. Define product direction across multiple ODP surfaces, including the control plane and data layer, by articulating clear problem statements and desired outcomes, and partnering with engineering on technical approach and sequencing Lead conversations with design partners and strategic customers to understand real-world platform pain points, validate product assumptions, and guide solutions from early prototypes through General Availability Develop a co