software engineer

on-site it support analyst Jobs in New York

on-site it support analyst

software developer

ai & genai data scientist-director Jobs in New York

ai & genai data scientist-director

ai training experts - new york Jobs in New York

ai training experts - new york

ai ml genai python developer onsite nj

HelloFresh

<div><h2 class="jobSectionHeader"><b>Senior Data Analyst</b></h2>
<p><b><i>
This is a hybrid role to our Newark, NJ HelloFresh facility</i></b></p>
<h2 class="jobSectionHeader"><b>
The role</b></h2>
<p>
As a Senior Data Analyst at HelloFresh, you will anchor the data strategy driving our aggressive, automation-first transformation. Our Global Customer Experience (GCX) team's mission is to understand our customers' journeys and empower market leads with insights and intelligent solutions that improve satisfaction, retention, and efficiency. We are moving fast to scale our self-serve rate, achieve 100% chatbot coverage, improve CSAT, and launch real-time, proactive incident communications via in-app CRM channels.</p>
<p>
We need a strategic thought partner for our Product, Engineering, and CX Automation teams who brings a high bar of technical rigor. In this role, you will own our core automation analytics architecture (chatbots, voicebots, agent-assist AI, and customer self-reporting tools), dive deep into GenAI conversational landscapes, and translate complex log data into actionable roadmap strategies. If you love solving open-ended problems and want to directly shape the experience of millions of global customers, you might just be our missing ingredient.</p>
<h2 class="jobSectionHeader"><b>
What you'll do</b></h2>
<ul><li>Anchor the data strategy for our entire automation and chatbot analytics infrastructure, serving as the sole embedded analytics lead within the Global CX department.</li>
<li>Proactively monitor user intents and trends to diagnose system bugs early and establish standardized, organization-wide KPIs for bot containment and NLP accuracy.</li>
<li>Conduct deep-dive analyses of chat transcripts and user journeys, leveraging semantic clustering and LLM evaluation to uncover friction points and tune conversational flows.</li>
<li>Continuously optimize and secure our reporting environment, ensuring data integrity, normalization, and advanced visualization techniques for critical executive decision-making.</li>
<li>Partner closely with cross-functional teams (Product, Engineering, and CX Automation) to translate complex customer log data and system requirements into sustainable roadmap strategies.</li>
<li>Own and deliver core business reporting mechanisms and dashboards, including the Monthly Business Review (MBR) and EBIT reviews.</li>
</ul><h2 class="jobSectionHeader"><b>What you'll bring</b></h2>
<ul><li>A passion for driving automation-first transformations and solving complex operational problems within a fast-paced customer experience environment.</li>
<li>Advanced proficiency in Python and SQL to handle increased domain complexity and secure our underlying reporting architecture.</li>
<li>Experience with next-gen agentic workflow stacks (e.g., Claude Code, Cursor) to optimize development and analytical speed.</li>
<li>Proven track record of designing, implementing, and maintaining high-visibility BI solutions and dashboards that communicate trends clearly to Directors, VPs, and SVPs.</li>
<li>Excellent communication and stakeholder management skills, with the confidence to lead complex data analytics projects and influence cross-functional partner</li></ul><br>
<p></p>
<h2 class="jobSectionHeader"><b>
You'll get</b></h2>
<ul><li><ul><li>Competitive Salary &amp; 401k company match that vests immediately upon participation</li>
<li>Generous parental leave of 16 weeks &amp; PTO policy, as well as paid holidays off</li>
<li>$0 monthly premium and other flexible health plans</li>
<li>Amazing discounts, including up to 85% off HelloFresh subscription</li>
<li>Emergency child and adult care services</li>
<li>Snacks &amp; monthly catered lunches</li>
<li>Collaborative, dynamic work environment within a fast-paced, mission-driven company</li></ul></li><br>
</ul>
<p></p><p>This job description is intended to provide a general overview of the responsibilities. However, the Company reserves the right to adjust, modify, or reassign work tasks and responsibilities as needed to meet changing business needs, operational requirements, or other factors.</p>
<div>
#data</div></div>

Senior Analyst - CX Automation Intelligence & Insights

Tessera Labs

<div>
 <strong>
  About Tessera Labs
  <br/>
  <br/>
 </strong>
 Tessera Labs is a new category of enterprise software: an AI platform that changes how the world's largest companies run.
 <br/>
 <br/>
 Every large enterprise carries the same weight &mdash; decades of accumulated process, data, and code that no longer match the business it has become. Changing any of it is a program measured in years and hundreds of millions of dollars, staffed by armies of consultants, and it fails more often than anyone admits. Most companies have quietly accepted this as the cost of being large.
 <br/>
 <br/>
 We don't. Tessera is a transformation engine: a governed, multi-agent platform that understands an enterprise's process, data, and code as one connected system and changes it in weeks rather than years. We're vendor-agnostic by design &mdash; SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft &mdash; and tied to none of them.
 <br/>
 <br/>
 Two things make this hard, and they're the reason the job is interesting. Governance: every action is logged, traceable, and reversible, because our customers are regulated and these are the systems that close their books. And generality: the platform has to work on landscapes it has never seen, at companies whose complexity is genuinely unique to them.
 <br/>
 <br/>
 <strong>
  We sell a product, not a service.
 </strong>
 Our people are here to make the product successful, not the other way around. If you've watched enterprise AI companies quietly become consultancies, that distinction is the one to press us on.
 <br/>
 <br/>
 We raised a $60M Series A led by Andreessen Horowitz, with Foundation Capital, Myriad Venture Partners, and Osage University Partners participating.
 <br/>
 <br/>
 <strong>
  About The Role
  <br/>
  <br/>
 </strong>
 Turning platform capability into outcomes a Fortune 500 will bet on has two halves &mdash; the systems that surround the model, and the model itself. This role owns the first.
 <br/>
 <br/>
 You will own agents end to end: the harness they run in, the tools they call, the context they see, the guardrails around them, and the evals that tell us whether any of it is improving. Most of the difficulty is not model access. It's an agent reasoning across a landscape with nineteen years of undocumented decisions embedded in it, where one call silently returns a stale schema forty steps into a plan &mdash; and the work of making that failure legible, reproducible, and then impossible.
 <br/>
 <br/>
 This is not a prototyping role. Everything you build gets pointed at systems a company's quarter close depends on.
 <br/>
 <br/>
 <em>
  If the model itself interests you more than the systems around it, look at Research Engineer &mdash; same team, other half of the problem.
  <br/>
  <br/>
 </em>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and ship the production agents that do transformation work: understanding a landscape, planning a change, executing it across process, data, and code, and proving it was correct.
  </li>
  <li>
   Build the tool layer &mdash; typed, permissioned, well-documented interfaces that let agents read and act across enterprise systems without ever exceeding what a human approver authorized.
  </li>
  <li>
   Improve agent performance through prompting, context construction, tool-use strategy, and decision logic &mdash; and know which of those a given failure calls for.
  </li>
  <li>
   Build the retrieval layer over enterprise artifacts and metadata: chunking and indexing strategies for content that doesn't resemble prose, hybrid search, reranking, grounding, and the evaluation that tells you whether any of it helped.
  </li>
  <li>
   Manage context deliberately. Enterprise artifacts are enormous and a forty-step run accumulates history fast; deciding what the model sees, what gets compressed, and what gets dropped is a first-class engineering problem here, not a prompt detail.
  </li>
  <li>
   Use classical ML where it's the right tool. Plenty of the work inside an agent pipeline &mdash; routing, ranking, classification, anomaly detection, confidence estimation &mdash; is better served by a small supervised model than by another LLM call, and knowing the difference is part of the job.
  </li>
  <li>
   Build the eval and monitoring layer: task sets drawn from real customer landscapes, regression coverage on every deploy, and alerting that catches a changed schema, a revoked authorization, or a new model version before the customer does.
  </li>
  <li>
   Instrument every run so each model call, tool invocation, decision, and human approval can be reconstructed afterward. This is what "passes audit" means in practice, and it's a product requirement rather than a nice-to-have.
  </li>
  <li>
   Diagnose production failures from execution traces down to root cause, then close the gap in the system rather than in a single prompt.
  </li>
  <li>
   Design the guardrails, approval gates, and rollback paths that make an agent safe to point at a live enterprise landscape.
  </li>
  <li>
   Build capability that generalizes. Anything that only works for one customer is a bug in the product, not a feature of the engagement.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Representative projects
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Shipping the agent that lets a customer retire a third of their custom estate in a quarter &mdash; and the review surface that makes a human comfortable approving each call in minutes rather than days.
  </li>
  <li>
   Designing the approval and write semantics for agents operating in a live landscape, so nothing reaches production without a traceable human decision and no partial failure leaves systems inconsistent.
  </li>
  <li>
   Building the reconciliation agent that makes two merged companies' data agree, plus the eval set that tells us when it's confident and when it's guessing.
  </li>
  <li>
   Standing up the replay-evaluation pipeline that scores a candidate agent version against a month of recorded runs &mdash; real system responses, mocked writes &mdash; so a regression is caught before anything is touched in a customer environment.
  </li>
  <li>
   Taking a pattern that worked at one customer and turning it into a platform primitive that works at the next four without a human rewriting it.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  You may be a good fit if you
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Have 3+ years building and operating production software, with meaningful recent time on LLM-powered systems.
  </li>
  <li>
   Have shipped agentic systems that real users depend on, and have owned the incident when they broke.
  </li>
  <li>
   Are fluent in the current agent toolkit &mdash; tool calling, orchestration, context engineering, RAG, evals, tracing &mdash; and can say where each one stops working.
  </li>
  <li>
   Have built retrieval systems against messy real-world corpora, and have measured them rather than assumed them.
  </li>
  <li>
   Have real traditional ML in your background &mdash; supervised learning, feature engineering, model evaluation &mdash; and reach for it when it beats a prompt.
  </li>
  <li>
   Treat evaluation as engineering rather than a report you generate at the end.
  </li>
  <li>
   Think in systems and customer outcomes, not model metrics.
  </li>
  <li>
   Are comfortable with non-determinism and have opinions about building reliably on top of it.
  </li>
  <li>
   Write strong Python and are comfortable in TypeScript.
  </li>
  <li>
   Ship fast, and verify before you claim it works.
  </li>
  <li>
   Find large, ugly, undocumented enterprise systems interesting rather than beneath you. That instinct is most of the job, and it's rarer than it should be.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Strong candidates may also have
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Hands-on experience with enterprise platforms, their APIs, and their extension models &mdash; SAP, Salesforce, Workday, Oracle, Snowflake, MuleSoft, ServiceNow.
  </li>
  <li>
   Experience with knowledge graphs, ontologies, or semantic models over messy real-world systems.
  </li>
  <li>
   Experience with code analysis, program transformation, or automated refactoring at scale.
  </li>
  <li>
   Experience with MCP, sub-agents, or agent skill/plugin architectures.
  </li>
  <li>
   A background in distributed systems or workflow engines, where partial failure is the default case.
  </li>
  <li>
   Experience at an early-stage startup or as a founder, where scope was whatever needed doing that week.
  </li>
  <li>
   Familiarity with enterprise security and compliance realities: SSO, RBAC, segregation of duties, PII handling, SOC 2, data residency.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Join the Future of AI at Tessera Labs
  <br/>
  <br/>
 </strong>
 We're looking for someone who enjoys building reliable, scalable systems that help teams move faster. If you take pride in cutting-edge AI, value clear ownership, and want to have a meaningful impact in a fast-moving environment, you&rsquo;ll fit right in.
 <br/>
 <br/>
 No third party may recruit, solicit candidates, publish job opportunities, use Tessera Labs&rsquo; name or branding, or represent that they are acting on behalf of Tessera Labs without prior written authorization. Any such activity conducted without explicit written consent is strictly prohibited.
 <br/>
 <br/>
 Compensation Range: $200K - $250K
 <br/>
 <br/>
</div>


AI Engineer

Qureos

<p><strong>About the company:</strong></p><p> </p><p>We build AI hiring agents. They deploy inside the enterprise systems a company already runs, or on the Qureos platform itself for teams who would rather have the whole hiring stack in one place. Either way the agents do the work recruiting teams have always done by hand, from sourcing and screening to interviewing and shortlisting, with speed and consistency no agency or traditional ATS can match. We are a Seed-stage startup backed by Prosus Ventures and COTU Ventures, having raised $5M to accelerate the future of AI-powered hiring. Trusted by more than 1,000 enterprise and public sector organizations, we're scaling rapidly as we build the next generation of AI hiring agents. Operating in a market where every unfilled role and every slow hiring loop costs real money, we are building the future of AI-powered hiring. Our agents let companies run high-volume hiring end to end without ripping out the systems their teams already live in.</p><p> </p><p><strong>About the Role</strong></p><p> </p><p>As a Forward Deployed Engineer, you will sit at the intersection of engineering, AI, and customer impact. You will work directly with customers to understand how they hire, find the parts of that process worth handing to an agent, and then design, build, and deploy those agents either into the customer's existing enterprise stack or onto the Qureos platform, depending on how they want to run.</p><p> </p><ul><li>You will partner closely with customers and Qureos's product and engineering teams to customise agent workflows, improve agent performance, and bring what you learn in live deployments back into the core platform.</li><li>This role is ideal for an engineer who enjoys building production systems, working inside someone else's environment, solving ambiguous problems, and shaping how AI actually gets used in hiring.</li></ul><p> </p><p>What You'll Do</p><p> </p><ul><li>Embed directly with customers to understand their hiring processes, the systems those processes run on, and where an agent can take over.</li><li>Design, build, and deploy AI hiring agents that source, screen, interview, and move candidates through the funnel.</li><li>Ship those agents into the customer's existing enterprise environment, or onto the Qureos platform for customers who want the all-in-one setup.</li><li>Develop and maintain the infrastructure behind the agents, including APIs, integrations with enterprise ATS and HRIS systems, monitoring, and feedback loops.</li><li>Translate customer requirements into scalable technical solutions and production-ready deployments.</li><li>Collaborate with product and engineering teams to influence roadmap decisions based on what you see in the field.</li><li>Identify patterns across customer deployments and turn one-off integration work into something the platform supports natively.</li><li>Work across engineering, product, and customer teams to ensure successful adoption and long-term impact.</li><li>Operate independently in fast-moving environments where ownership and initiative are highly valued.</li></ul><p> </p><p><strong>What You'll Bring</strong></p><p> </p><ul><li>3+ years of software engineering experience, preferably with backend, infrastructure, or systems-focused development.</li><li>Strong programming experience in Python (experience with TypeScript/JavaScript is a plus).</li><li>Experience working with cloud platforms such as AWS, GCP, or Azure.</li><li>Ability to design and build reliable production systems, including inside environments you do not control.</li><li>Strong communication skills with the ability to work with both technical and non-technical stakeholders.</li><li>Experience working directly with customers, partners, or cross-functional teams is a plus.</li></ul><p> </p><p><strong>Bonus</strong>: experience with AI agents, large language models (LLMs), vector databases, prompt engineering, retrieval-augmented generation (RAG), voice agents, or integrating with enterprise ATS and HRIS platforms.</p><p> </p><p>Comfortable working in dynamic environments with changing priorities and high ownership.</p><p> </p><p><strong>Why Join Us</strong></p><p> </p><p>You'll be part of a team building a category-defining AI company in a market that has barely started to change. We move fast, we ship, and we work close to the customer.</p><p> </p><p>If you are excited about building AI agents that do real work, deploying them into the systems enterprises actually run, and shaping how hiring gets done, we'd love to hear from you.</p>

Forward Deployed Engineer

Ameriprise Financial

<div><p><b>About Our Company</b></p><p><br>
We&rsquo;re a diversified financial services leader with more than $1.5 trillion in assets under management, administration and advisement as of year-end 2024. Our team of 22,000 people across 19 countries, serves more than 3.5 million individual, small business and institutional clients. We are a longstanding leader in financial planning and advice, a global asset manager and an insurer. Our unwavering focus on our clients and strong financial foundation connects each of our unique businesses &ndash; Ameriprise Financial, Columbia Threadneedle Investments and RiverSource Insurance and Annuities. Here, we foster meaningful careers, invest in the future, and make a difference for clients, institutions and communities around the world.</p><p></p><p><b>
Job Description</b></p><p></p>
The VP-Forward Deployed Engineer operates at the intersection of investment strategy, quantitative analysis and applied artificial intelligence. The position is responsible for partnering closely with portfolio management and investment research teams to identify opportunities, design solutions, and develop, prototype, and deploy LLM-enabled tools that enhance investment decision-making and research processes. Combines investment management knowledge with software engine capabilities to translate investment ideas and research needs into scalable technology solutions.<p></p><p><b>
Key Responsibilities</b></p><ul><li>
Serve as a trusted advisor to investment leaders, translating investment strategies, research priorities, and business challenges into innovative AI-enabled solutions that improve investment outcomes and organizational efficiency.</li><li>
Drive the design and delivery of proof-of-concept and production-ready AI capabilities, leveraging advanced analytics, machine learning, and LLM technologies to accelerate investment insights and decision-making.</li><li>
Partner across Investments, Technology, Data, Risk, and Compliance functions to ensure solutions meet enterprise standards for security, governance, scalability, and regulatory compliance.</li><li>
Influence the AI and investment technology roadmap by identifying high-value opportunities, evaluating emerging capabilities, and promoting adoption of innovative solutions across the investment organization.</li><li>
Lead the transition of successful prototypes into sustainable enterprise capabilities, partnering with engineering and platform teams to scale solutions and realize long-term business value.</li></ul><p><b><br>
Required Qualifications</b></p><ul><li>
10+ years of combined experience across investment management, quantitative research/strategy, and hands-on software or AI engineering, with demonstrated success taking investment problems from concept to working solution.</li><li>
Direct experience working alongside trading desks, portfolio managers, or investment researchers, with desk strategist, quant strat, or research technologist backgrounds strongly preferred.</li><li>
Hands-on experience building and shipping LLM enabled/integrated applications: RAG/embeddings, agentic workflows, prompt engineering, API integration.</li><li>
Strong Python development skills producing production-quality code.</li><li>
Expertise with cloud infrastructure and modern software practices (CI/CD, version control, API design).</li><li>
Fluency in at least one asset class (equities, fixed income, multi-asset, or macro) at a level where you can challenge and contribute to investment discussions, not just support them.</li><li>
Track record of delivering secure, auditable AI solutions in a regulated environment, partnering with risk and compliance.</li></ul><p><b><br>
Preferred Qualifications</b></p><ul><li>
Direct experience supporting front-office investment teams (portfolio managers, analysts, researchers, traders).</li><li>
Familiarity with agent frameworks and orchestration tools (LangChain, LangGraph, LlamaIndex, MCP) and vector databases.</li><li>
Experience building internal copilots, research assistants, or document-intelligence tools.</li><li>
CFA, FRM, or equivalent investment credential.</li><li>
Track record of shipping AI or analytics solutions that produced measurable, real-world outcomes.</li></ul><p></p><p><b>
Visa Sponsorship</b><br>
Applicants must have a valid work authorization that does not now, or in the future, require visa sponsorship for employment in the United States (e.g., H-1B, F-1 CPT, F-1 OPT, TN).</p><p></p><p><b>
In-Office Collaboration</b><br>
We are a client-centric, relationship-based business. Working together, in-person, is foundational to how we achieve results. By fostering a culture of face-to-face collaboration, idea sharing, productivity and personal connection, we deliver for our stakeholders &mdash; clients, advisors, employees and shareholders. Our employees work in the office at least four (4) days per week, with flexibility to work from home one (1) day per week. Some roles may require additional in-office time or different in-office expectations, and specific requirements will be discussed during the hiring process.</p><p></p><p><b><br>
Base Pay Salary</b></p><p></p>
The estimated base salary for this role is $242,100 - $332,900 / year. We have a pay-forperformance compensation philosophy. Your initial total compensation may vary based on job-related knowledge, skills, experience, and geographical work location. In addition, most of our roles are eligible for variable pay in the form of bonus, commissions, and/or long-term incentives depending on the role. We also have a competitive and comprehensive benefits program that supports all aspects of your health and well-being, including but not limited to vacation time, sick time, 401(k), and health, dental and life insurances.<p></p><div><div><div><div><div><div><div><p><b>
Full-Time/Part-Time</b></p></div></div></div></div></div></div></div>
Full time<p></p><div><div><div><div><div><div><div><p><b>
Exempt/Non-Exempt</b></p></div></div></div></div></div></div></div>
Exempt<p></p><div><div><div><div><div><div><div><p><b>
Job Family Group</b></p></div></div></div></div></div></div></div>
Data<p></p><div><div><div><div><div><div><div><p><b>
Line of Business</b><b>
</b></p></div></div></div></div></div></div></div>TECH Technology<p></p><p><i>
Ameriprise Financial is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, ancestry, age, physical or mental disability, medical condition, pregnancy, military status, veteran status, genetic information, citizenship, disability status, marital status, family status or any other basis prohibited by law.</i></p><p></p><p><i>
We are committed to fostering an inclusive and accessible recruitment process for individuals with disabilities. If you require a reasonable accommodation to participate in the application or interview process, speak to your recruiter to discuss how we can support you.</i></p></div>

Vice President - Forward Deployed Engineer

Progyny

<div><p>Thank you for considering Progyny!</p><p></p><p>
We are hiring a Manager, Medical Economics &amp; Analytics to join our team in New York City. This role will primarily support the Operations team.</p><p>
Our team develops data, analytical insights, and tools that support Progyny&rsquo;s internal operations and help drive an exceptional member and provider experience. In this role, you&rsquo;ll partner closely with cross-functional teams, including Provider Network, Claims, Contact Center, and Member Experience, to deliver analyses and solutions that improve operational performance and inform strategic decision-making. You&rsquo;ll also work closely with Data Engineering and IT partners to advance our analytics infrastructure, expand AI-enabled capabilities, and build scalable solutions that enable teams across the organization to make better data-driven decisions.</p><p></p><p><b>
What You'll Do...</b></p><ul><li><p>
Become a subject matter expert (SME) in Progyny claims, utilization, provider network, operational, and financial data, translating complex datasets into actionable insights that improve business performance.</p></li><li><p>
Lead, develop, and mentor a team of analysts responsible for delivering high-quality analyses, reporting, and analytical solutions to key operational stakeholders.</p></li><li><p>
Build, maintain, and optimize scalable analyses, data models, dashboards, and reporting using SQL, Excel, and modern analytics and visualization tools.</p></li><li><p>
Partner closely with cross-functional operational teams, including Provider Network, Claims, Contact Center, and Member Experience, to identify opportunities, evaluate performance, develop KPIs, and deliver insights that inform operational and strategic decision-making.</p></li><li><p>
Partner with Data Engineering and other IT teams to help shape and advance Progyny&rsquo;s analytics infrastructure and data strategy, including data models, pipelines, tooling, governance, and self-service analytics capabilities.</p></li><li><p>
Identify opportunities to improve analytical workflows, automate manual processes, and drive cross-functional initiatives that increase operational efficiency and enable scalable, data-driven decision-making<b>.</b></p></li></ul><p></p><p><b>
About You...</b></p><ul><li><p>
Bachelor's degree with an analytical focus in healthcare, economics, finance, statistics, data analytics, or a related field.</p></li><li><p>
5&ndash;7 years of relevant experience in healthcare, insurance, consulting, analytics, or a related field, including 1&ndash;3 years of people management experience.</p></li><li><p>
Advanced SQL skills with demonstrated experience querying, transforming, and analyzing large and complex datasets (30M+ rows).</p></li><li><p>
Experience working with modern data platforms and transformation tools such as AWS, dbt, Databricks, or similar technologies.</p></li><li><p>
Proficiency with data visualization and business intelligence tools such as Tableau, Power BI, Looker, or similar platforms, with demonstrated experience developing effective dashboards and data products for business stakeholders.</p></li><li><p>
Advanced analytical and problem-solving skills with the ability to translate ambiguous business questions and complex datasets into structured analyses, clear insights, and actionable recommendations.</p></li><li><p>
Familiarity with healthcare and insurance terminology, provider networks, healthcare operations, and medical or pharmacy claims data.</p></li><li><p>
Demonstrated experience leading, coaching, and developing analysts while establishing priorities, maintaining high standards for analytical quality, and creating an environment of continuous learning.</p></li><li><p>
Experience working in modern analytics environments and IDEs (e.g., Visual Studio Code, Cursor, PyCharm, or similar) and using AI-enabled tools to accelerate analysis, development, or workflows.</p></li><li><p>
Ability to partner effectively with Data Engineering and technical teams to define data requirements, improve analytical infrastructure, and develop scalable data and reporting solutions.</p></li><li><p>
Excellent time and project management skills with the ability to prioritize competing requests, manage multiple initiatives simultaneously, and deliver high-quality work under tight deadlines.</p></li><li><p>
Self-motivated and comfortable operating independently, navigating ambiguity, and taking ownership of analytical initiatives from problem definition through implementation.</p></li><li><p>
Advanced written and verbal communication skills, with the ability to explain complex analytical concepts to non-technical stakeholders, influence cross-functional partners, and communicate effectively with senior leadership.</p></li></ul><p></p><p><b>
Please note: </b>This is not a digital nomad or remote international position; candidates must be based in the United States. Progyny is unable to provide visa sponsorship for this position. Candidates must be authorized to work in United States without the need for sponsorship, now or in the future.
</p><p></p><p><b>About Progyny:</b>
</p><p>Progyny (Nasdaq: PGNY) is a global leader in women&rsquo;s health and family building solutions, trusted by the nation&rsquo;s leading employers, health plans and benefit purchasers. We envision a world where everyone can realize dreams of family and ideal health. Our outcomes prove that comprehensive, inclusive and intentionally designed solutions simultaneously benefit employers, patients and physicians.</p><p></p><p>
Our benefits solution empowers patients with concierge support, coaching, education, and digital tools; provides access to a premier network of fertility and women's health specialists who use the latest science and technologies; drives optimal clinical outcomes; and reduces healthcare costs.</p><p></p><p>
Our mission is to empower healthier, supported journeys through transformative fertility, family building and women&rsquo;s health benefits.</p><p></p><p>
Headquartered in New York City, Progyny has been recognized for its leadership and growth as a TIME100 Most Influential Company, CNBC Disruptor 50, Modern Healthcare's Best Places to Work in Healthcare, Forbes' Best Employers, Financial Times Fastest Growing Companies, Inc. 5000, Inc. Power Partners, and Crain's Fast 50 for NYC. For more information, visit www.progyny.com.</p><p></p><p><b>
Our perks:</b>
</p><ul><li><p>Family friendly benefits: Paid family and parental leave, preconception, fertility and family building benefits (including egg freezing, IVF, and adoption support), family and pet care fund, and Parents&rsquo; Employee Affiliation Group</p></li><li><p>
Menopause and midlife care</p></li><li><p>
Health, dental, vision and life insurance options for employees and family</p></li><li><p>
Free in-person, virtual and text-based mental health and wellness support
</p></li><li><p>Paid time off, including vacation, sick leave, personal days and summer flex time</p></li><li><p>
Company equity</p></li><li><p>
Bonus program</p></li><li><p>
401(k) plan with company match</p></li></ul><ul><li><p>
Access to on-demand legal and financial advice</p></li><li><p>
Learning and development programs to help you grow professionally and a mentorship program</p></li><li><p>
Company social events to include annual volunteer day and donation matching</p></li><li><p>
Flex days (3 days a week in the office) and onsite meals and snacks for employees reporting into our NY office</p></li></ul><p></p><p>
In compliance with New York City's Wage Transparency Law, the annual salary [wage] range for NYC-based applicants is:<b> $130,000 - $145,000.</b> There are a variety of factors that go into determining a salary range, including but not limited to external market benchmark data, geographic location, and years of experience sought/required. Progyny offers a total compensation package comprised of base salary, cash bonus, and equity.
</p><p></p><p>Progyny is proud to be an Equal Opportunity and Affirmative Action employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce. All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability, age, genetic information, marital status, pregnancy or related condition, status as a protected veteran, criminal history consistent with legal requirements or any other basis protected by law.</p><p></p><p>
If you are an individual with a disability and need assistance or an accommodation during the recruiting process, please send an e-mail to apply@progyny.com.</p><p>
#LI-BG1</p></div>

Manager, Medical Economics & Analytics

SERVAL

<div><h1 class="jobSectionHeader"><b>Who We Are</b></h1><p>
Serval is an AI-native automation platform transforming how enterprises operate. We build intelligent agents that understand real-world workflows and execute them end-to-end &mdash; replacing manual processes and rigid legacy systems with adaptive, learning software. Founded in early 2024, Serval is already trusted by companies like Fox, Notion, Perplexity, Vercel, and Brex to automate high-volume, high-friction operational work across their organizations.<br>
<br>
At the core of Serval is an agentic AI platform that turns natural language into production-grade workflows. Our agents don&rsquo;t just respond to requests &mdash; they reason, take action across systems, and continuously improve with usage. What began with operational use cases has quickly evolved into a horizontal AI automation layer used across IT, HR, Finance, Security, Legal, and Engineering.<br>
<br>
Our mission is to eliminate repetitive, manual work across the enterprise and give teams leverage through intelligent automation. Long term, we&rsquo;re building the universal AI operations layer &mdash; a system of agents that sits across business functions and runs the workflows that keep modern companies moving.<br>
<br>
We&rsquo;re backed by leading investors including Sequoia Capital, Redpoint Ventures, Meritech, First Round, General Catalyst, Elad Gil, and others.
</p><p></p><h1 class="jobSectionHeader"><b>About the team</b></h1><p>
The <b>Agent Deployment</b> team is a customer-facing technical team, central to how Serval turns product capability into real business outcomes. The org is a family of roles: Deployment Strategists are the primary technical relationship and AI advisor for each customer, partnering with Deployed Software Engineers to build enterprise-grade features and products. Deployment Success Managers own each customer's long-term success, building the systems and motions that scale adoption, expansion, and renewal well past go-live.</p><h1 class="jobSectionHeader"><b><br>
Role Overview</b></h1><p>
As a Deployment Strategist on Serval's Agent Deployment team, you&rsquo;ll be the primary technical relationship for Serval&rsquo;s customers: guiding their deployments, advising their AI strategy, and owning their outcomes. You&rsquo;ll work deeply within Serval&rsquo;s existing product surface area: building novel workflows, configuring integrations, and shipping bug fixes and product changes yourself.</p><p>
This role is for someone who thrives on execution velocity, moving quickly across multiple engagements at once. You&rsquo;re at home in ambiguity and bring a strong blend of technical depth, product sense, and customer obsession. And because you sit closest to how customers actually use Serval, you'll directly shape our product roadmap: the workflows and features you build in the field make their way into the core product.</p><p></p><h1 class="jobSectionHeader"><b>
What You&rsquo;ll Do</b></h1><ul><li><p><b>
Own customer engagements from pilot through production launch: </b>design and deliver deployments that fit each customer's workflows and scale adoption of Serval.</p></li><li><p><b>
Build AI agents:</b> design and build AI agents on Serval's platform that drive real value for customers.</p></li><li><p><b>
Advise AI strategy:</b> embed with customers to guide and shape how they adopt and scale AI.</p></li><li><p><b>
Lead migrations:</b> design and execute migration plans that minimize disruption and ensure seamless adoption of Serval's platform.</p></li><li><p><b>
Partner cross-functionally:</b> work with Engineering, Sales, and Marketing to turn field learnings into repeatable processes and a sharper go-to-market.</p></li></ul><p></p><h1 class="jobSectionHeader"><b>
What You&rsquo;ll Need</b></h1><ul><li><p>
Degree in Computer Science or a related field, or equivalent hands-on experience.</p></li><li><p>
5+ years in a relevant role (product, engineering, consulting, founder).</p></li><li><p>
Strong communication and relationship management skills, with the ability to translate complex technical concepts for both technical and non-technical stakeholders.</p></li><li><p>
Hands-on technical ability: reading and troubleshooting production code in customer-facing environments, analyzing code paths, database state, and API requests/responses with infra and browser dev tools.</p></li><li><p>
Working knowledge of APIs and REST, IAM, and SQL for data analysis.</p><div><br>
</div></li></ul><h1 class="jobSectionHeader"><b>
Nice to Have</b></h1><ul><li><p>
Experience in an early-stage startup environment.</p></li><li><p>
Experience writing production code.</p></li><li><p>
Background working with enterprise customers or complex technical sales cycles.</p></li><li><p>
Familiarity with IT, security, service management, or workflow automation.</p></li></ul><p></p><h2 class="jobSectionHeader"><b>
What We Offer</b></h2><ul><li><p><b>
Impact</b>: Be a key player in shaping the success of our product and company.</p></li><li><p><b>
Growth</b>: Build a fundamentally new AI product offering with the support of our experienced team and investors. Grow rapidly with the company.</p></li><li><p><b>
Culture</b>: Join a culture that values innovation, ownership, accountability, and fun.</p></li></ul><p>
Compensation Range: $150K - $280K</p></div>

Deployment Strategist

Product Marketing Lead, Instagram Reels Monetization and Ads Experiences

Explore 9+ Ai ml genai python developer onsite nj in New York this August. Find roles across top companies and apply now to boost your career.