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applied ai health data system engineer senior manager

<div><div><div><div><div><div>Job ID</div>
<div>727748WD</div>
</div><div><div>Category</div>
<div>Data and Analytics Engineering</div>
</div><div><div>Time Type</div>
<div>Full time</div>
</div><div><div>Specialty/Competency</div>
<div>Data, Analytics &amp; AI</div>
</div><div><div>Level</div>
<div>Senior Manager</div>
</div><div><div>Travel Requirements</div>
<div>Up to 80%</div>
</div><div><div>Locations</div>
<div>New York, Raleigh, Charlotte, Chicago, Cincinnati, Cleveland, Columbia, Columbus, Dallas, Richmond, Baltimore, Rochester, Rosemont, Boston, Sacramento, St Louis, Salt Lake City, San Antonio, San Diego, San Francisco, Silicon Valley, Seattle, Spartanburg, Stamford, Tampa, Toledo, Atlanta, Tulsa, Austin, Washington D.C., Denver, Des Moines, Detroit, Buffalo, Florham Park, Fort Worth, Greensboro, Hartford, Houston, Indianapolis, Grand Rapids, Irvine, Jacksonville, Kansas City, Las Vegas, Little Rock, Los Angeles, Louisville, Birmingham, Fayetteville, Melville, Miami, Milwaukee, Minneapolis, Nashville, New Orleans, Oklahoma City, Philadelphia, Phoenix, Pittsburgh, Portland</div>
</div></div></div><div><div> 
At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
 
 
Those in artificial intelligence and machine learning at PwC will focus on developing and implementing advanced AI and ML solutions to drive innovation and enhance business processes. Your work will involve designing and optimising algorithms, models, and systems to enable intelligent decision-making and automation.
 
 
Growing as a strategic advisor, you leverage your influence, expertise, and network to deliver quality results. You motivate and coach others, coming together to solve complex problems. As you increase in autonomy, you apply sound judgment, recognising when to take action and when to escalate. You are expected to solve through complexity, ask thoughtful questions, and clearly communicate how things fit together. Your ability to develop and sustain high performing, diverse, and inclusive teams, and your commitment to excellence, contributes to the success of our Firm.
 
 
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
 
 
Craft and convey clear, impactful and engaging messages that tell a holistic story.
 systems thinking to identify underlying problems and/or opportunities.
 
Validate outcomes with clients, share alternative perspectives, and act on client feedback.
 
Direct the team through complexity, demonstrating composure through ambiguous, challenging and uncertain situations.
 
Deepen and evolve your expertise with a focus on staying relevant.
 
Initiate open and honest coaching conversations at all levels.
 
Make difficult decisions and take action to resolve issues hindering team effectiveness.
 
Model and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
 
 
The Opportunity
 
 
As part of the Applied AI Health System Engineering team, you will lead the development of AI, GenAI, and ML solutions tailored to the complex needs of health system and health plans. As a Senior Manager, you will drive use case development across clinical decision support, population health risk stratification, clinical research, and operational efficiency &mdash; translating ambiguous healthcare challenges into production-grade AI solutions. You will architect and build production-grade RAG pipelines, MCP connections, agentic AI workflows, and MLOps frameworks, managing daily operations across global delivery teams while engaging health system leaders at the executive level to ensure measurable clinical and operational impact.
 
 
Responsibilities
 
 
<ul><li>Oversee the development of healthcare AI and GenAI solutions, including clinical use case design, analytical modeling, prompt engineering, and RAG pipeline development
</li><li>Lead large healthcare data science engagements, innovating delivery processes and driving continuous improvement across use case development lifecycles
</li><li>Maintain operational excellence while engaging health system clinical, financial, and operational leaders at a senior level to align AI initiatives with organizational priorities
</li><li>Guide teams in processing clinical notes, claims data, ADT feeds, and other structured and unstructured healthcare data sources for use in AI and LLM-powered solutions
</li><li>Manage daily operations of a global healthcare data science team, overseeing model development, MLOps practices, and model governance across client engagements
</li><li>Contribute to the creation of healthcare AI proof of concepts, pilots, and production use cases spanning clinical decision support, revenue cycle, population health, research (including images and genomics) and operational optimization
</li><li>Foster a collaborative environment across clinical, technical, and operational team members to solve complex health system data science challenges
</li><li>Maintain excellence in client service and satisfaction, helping health system clients realize tangible value from AI and ML investments
</li></ul> 
What You Must Have
 
 
<ul><li>Bachelor's Degree
</li><li>12 years of experience, with meaningful exposure to healthcare data science, health IT, or AI solution development for health system clients
</li><li>At least 6-7 years of experience at a health system
</li></ul> 
Preferred Knowledge/Skills
 
 
Demonstrates in-depth level abilities and/or a proven record of success managing the identification and addressing of health system needs
 
 
Domain expertise in the healthcare value chain including but not limited to Claims, Pharmacy, Finance, Clinical Domains
 
 
Managing development teams in building healthcare AI and GenAI solutions, including analytical modeling, prompt engineering, Python-based development, testing, communication of results to clinical and operational stakeholders, front-end and back-end integration, and iterative use case development with health system clients;
 
 
Documenting and analyzing healthcare business processes &mdash; across clinical operations, and population health programs &mdash; to identify AI and GenAI opportunities, gather requirements, define initial hypotheses, and develop solution approaches tailored to health system workflows;
 
 
Collaborating with health system client teams &mdash; including clinical informatics, population health, and IT leaders &mdash; to understand their business and clinical problems and select the appropriate models, LLMs, and approaches for AI/GenAI use cases;
 
 
Designing and solutioning AI/GenAI architectures for health system clients, including RAG-based clinical knowledge retrieval systems, agentic AI workflows for care management and revenue cycle automation, and custom LLM application builds with appropriate PHI safeguards;
 
 
Managing teams to process healthcare unstructured and structured data &mdash; including clinical notes, discharge summaries, claims records, EHR data, and ADT feeds &mdash; for use as LLM context, including embedding of large clinical text corpora, generative SQL query development, and building connectors to EHR back-end databases;
 
 
Managing daily operations of a global healthcare data science team on client engagements, reviewing developed models, providing feedback, and assisting in analysis of clinical and operational outcomes;
 
 
Directing data engineers and other data scientists to deliver efficient, HIPAA-compliant solutions that meet health system client requirements for clinical, financial, and operational AI use cases;
 
 
Leading and contributing to development of proof of concepts, pilots, and production use cases for health system clients &mdash; spanning clinical decision support, prior authorization automation, patient risk scoring, workforce optimization, and throughput modeling &mdash; while working in cross-functional teams;
 
 
Facilitating and conducting executive-level presentations to health system leadership showcasing GenAI and ML solution capabilities, use case development progress, model performance, and recommended next steps;
 
 
Structuring, writing, communicating, and facilitating client presentations that translate complex AI and ML concepts into clear clinical and business value narratives for health system audiences; and,
 
 
Managing associates and senior associates through coaching, providing feedback, and guiding work performance, with an emphasis on developing healthcare domain knowledge alongside technical AI and ML capabilities.
 
 
Demonstrates in-depth abilities and/or a proven record of success learning and performing in functional and technical capacities within healthcare data science and AI, including the following areas:
 
 
Managing GenAI application development teams building healthcare-facing solutions, including back-end LLM orchestration, agentic workflow design, and front-end integration with clinical and operational portals;
 
 
Using Python (e.g., Pandas, Scikit-learn, Keras, Transformers) and common LLM development frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel) to build healthcare AI solutions; proficiency with relational storage (SQL, including clinical schemas and non-relational storage (NoSQL, vector databases such as Pinecone or Chroma for RAG pipelines);
 
 
Experience in analytical techniques including Machine Learning, Deep Learning, and Optimization applied to healthcare use cases such as risk stratification, readmission prediction, clinical coding automation, length-of-stay modeling, and staffing/scheduling optimization;
 
 
Vectorization and embedding of clinical text, prompt engineering for healthcare contexts, RAG (retrieval-augmented generation) workflow development for clinical knowledge retrieval, and design of agentic AI workflows for multi-step healthcare processes such as prior authorization, care gap identification, and revenue cycle task automation;
 
 
Hands-on experience with Azure (including Azure OpenAI Service, Azure Machine Learning, and Azure Health Data Services), AWS (SageMaker, Bedrock), and/or Google Cloud (Vertex AI) platforms, with an understanding of PHI-compliant deployment patterns and HIPAA-aligned cloud configurations;
 
 
Experience with data warehouse technology including Snowflake or Databricks
 
 
Experience working with Anthropic &ndash; Claude and Claude code to accelerate development and build applications
 
 
Experience with Git version control, unit/integration/end-to-end testing, CI/CD, and MLOps practices including model monitoring, performance drift detection, and model governance frameworks appropriate for regulated healthcare environments.
 
 
What Sets You Apart
 
 
<ul><li>Demonstrated experience delivering production AI or GenAI use cases in a health system environment, with measurable clinical or financial outcomes
</li><li>Hands-on experience building RAG pipelines or agentic AI workflows against clinical data sources, including EMR
</li><li>Experience with MLOps platforms and model governance practices in regulated, PHI-handling environments
</li><li>Ability to translate clinical and revenue cycle workflows into structured AI use case requirements and scalable solution designs
</li><li>Familiarity with Azure OpenAI Service, AWS Bedrock, or Google Vertex AI in a HIPAA-compliant deployment context
</li><li>Understanding of value-based care, population health program design, or clinical quality measurement and how AI accelerates outcomes in these areas 
</li></ul> 
 
The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance
As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.
PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.
Learn more about how we work: https://pwc.to/how-we-work
For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.
Applications will be accepted until the position is filled or the posting is removed, unless otherwise set forth on the following webpage. Please visit this link for information about anticipated application deadlines: https://pwc.to/us-application-deadlines
 
 
#LI-Hybrid</div></div></div></div>

Applied AI Health Data System Engineer-Senior Manager

REGAL

<div>
 
 ABOUT US:
 
 
 Founded in 2020, Regal is the AI Agent Platform. Regal gives every company the tools to transform customer communications with delightful AI Agents that are connected to your data, easy to customize and monitor, always available, and ready to take action. Power better support, sales, and operations - with way less effort. Our founders, Alex Levin and Rebecca Greene, helped build Angi (Angie&rsquo;s List, HomeAdvisor, and Handy) to over $1.5B in revenue.
 
 
 Based in Manhattan, we&rsquo;re building an in-person culture of entrepreneurs who want to win and build something meaningful. We&rsquo;re backed by top investors including Founder Collective, Homebrew, and Emergence Capital.
 
 
 Come join us as we create a category-defining company, and follow Regal's company page on LinkedIn to stay up-to-date on our journey and current job openings!
 
 
 We&rsquo;re moving fast, and the numbers speak for themselves:
 
 
 
 <ul>
 <li>
 Partnered with enterprise brands like Google, AAA, Ro, Coursera
 </li>
 <li>
 Raised $82M (top tier investors including Emergence &amp; Homebrew)
 </li>
 <li>
 Completed 500M+ calls
 </li>
 <li>
 Driven $7B revenue for customers
 </li>
 <li>
 Scaled to $##M ARR
 </li>
 <li>
 Built amazing NYC (Midtown) in office culture
 
 
 
 
 
 </li>
 </ul>
 
 ABOUT THE ROLE:
 
 
 We're hiring a Director of Engineering to own two of our most technically challenging areas: the real-time systems that power every live call, and the applied AI research that determines how those calls sound and feel.
 
 
 You'll lead two teams: one responsible for the real-time call delivery infrastructure that handles every live voice interaction at scale, and one doing proprietary model work on the problems that matter most to voice quality, end-of-utterance detection, voice activity detection, answering machine detection, and STT accuracy. These are active, production-impacting problems, not research projects.
 
 
 This is the right role for someone comfortable at the intersection of applied AI and real-time systems, not a pure researcher, and not a pure product EM. You'll work closely with Regal's Staff+ AI Engineering lead as a peer and collaborator, and you'll have room to grow into broader engineering ownership as the team scales.
 
 
 
 RESPONSIBILITIES:
 
 
 
 <ul>
 <li>
 Lead and develop engineers across two teams, set expectations, support career growth, and run a tight hiring bar. You thrive on managing people and view it as a privilege
 </li>
 <li>
 Own the technical roadmap for real-time call delivery and applied voice AI, in collaboration with Product, AI Engineering, and the broader eng leadership team
 </li>
 <li>
 Drive the applied AI roadmap: improving how AI agents talk to humans (pace, timing, accuracy, and warmth) and the contact center AI capabilities that make agents more effective in production
 </li>
 <li>
 Do whatever it takes to unblock your teams, whether that's changing a process, pair debugging, or cutting through cross-functional friction
 </li>
 <li>
 Work closely with product and engineering leadership to drive innovation and collaboration
 </li>
 <li>
 Maintain a strong peer relationship with Regal's AI Engineering lead, collaborative, not territorial. Applied model work intersects with research; managing that handoff well is part of the job
 </li>
 <li>
 Represent engineering in cross-functional conversations on voice quality, latency, and AI agent reliability
 </li>
 <li>
 Be actively involved in hiring: sourcing, interviewing, and onboarding
 
 
 
 
 
 </li>
 </ul>
 
 WHAT YOU'LL OWN:
 
 
 
 <ul>
 <li>
 Real-time call delivery: The systems that route, handle, and manage live voice calls. Telephony reliability, call delivery at scale. This team is the layer where every agent capability meets every customer
 </li>
 <li>
 Applied voice AI: Proprietary model work on the hardest voice quality problems: end-of-utterance (EOU) detection, voice activity detection (VAD), answering machine detection (AMD), STT accuracy, and p95 latency. Small team, high-leverage output
 
 
 
 
 
 </li>
 </ul>
 
 ABOUT YOU:
 
 
 
 <ul>
 <li>
 8+ years of experience in software engineering, with meaningful time in systems where latency and reliability are first-class constraints
 </li>
 <li>
 4+ years in engineering management, including experience managing mid to senior level engineers
 </li>
 <li>
 An entrepreneurial mindset, we're not looking for someone to run a playbook. We want you to help build it
 </li>
 <li>
 Comfortable operating at the boundary of research and engineering, you know how to take a model improvement and turn it into a production system, and vice versa
 </li>
 <li>
 Strong communication skills, you can translate complex technical tradeoffs for product stakeholders and work effectively with researchers
 </li>
 <li>
 Excellent judgment on prioritization, applied AI work is inherently exploratory; you know how to scope it against production impact
 
 
 
 
 
 </li>
 </ul>
 
 NICE TO HAVE:
 
 
 
 <ul>
 <li>
 Hands-on experience with STT/TTS pipelines, voice activity detection, or telephony infrastructure
 </li>
 <li>
 Prior work on latency-sensitive ML inference systems in production
 </li>
 <li>
 Experience with LLM orchestration or agent evaluation frameworks
 </li>
 <li>
 Familiarity with WebSockets, real-time audio, or WebRTC
 </li>
 <li>
 Prior startup experience at the Series B-D stage
 
 
 
 
 
 </li>
 </ul>
 
 Benefits/Perks
 
 
 
 <ul>
 <li>
 We care about your health!
 </li>
 <li>
 Medical, Dental, and Vision plans - 80% covered by the company
 </li>
 <li>
 Flexible PTO &amp; 11 paid holidays/year
 </li>
 <li>
 We care about future you!
 </li>
 <li>
 401k Plan
 </li>
 <li>
 Paid parental leave
 </li>
 <li>
 Pre-tax commuter benefits
 </li>
 <li>
 We care about connection!
 </li>
 <li>
 In-office breakfast and snacks daily
 </li>
 <li>
 Happy hours, team outings, &amp; annual off-sites
 </li>
 <li>
 Complete laptop workstation
 </li>
 <li>
 &amp; more to come!
 
 
 
 
 
 </li>
 </ul>
 
 POSITION LOCATION &amp; OFFICE DETAILS:
 
 
 This position is only available in New York City (HQ- Midtown). Hybrid roles are required in office T/W/TH and office optional M/F.
 
 
 
 <ul>
 <li>
 If you think you&rsquo;re missing relevant experience but you&rsquo;re hungry and a fast learner (and can prove it), we want to hear from you!
 
 
 
 
 
 </li>
 </ul>
 We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
 
 
 The reasonably estimated base salary for this role is provided as a range within this job description. All offers include a competitive equity package and some offers may additionally include a variable compensation component. Actual compensation is determined on an individualized basis taking into consideration factors such as the candidate's skills, location, qualifications, experience, and relevant education or training. In addition, Regal offers a comprehensive set of employee benefits which are listed above. Details about the compensation package will be finalized at the time of offer.
</div>

Director of Engineering

Inherent Technologies

<div>
 
 Job Description
 
 
 
 Seeking a
 
 hands-on AI Engineer/Developer
 
 to rapidly prototype and deliver AI-driven solutions across investment, research, and trading functions. This role is ideal for someone who can bridge
 
 financial domain knowledge with applied AI/ML development
 
 , building proof-of-concepts that can evolve into production-grade tools supporting investment decision-making.
 
 
 
 Key Responsibilities
 
 
 
 Design and develop
 
 AI/ML prototypes
 
 using Python to support investment research, portfolio analytics, and trading insights
 
 
 Build and test
 
 LLM-based and data-driven use cases
 
 (e.g., research summarization, signal generation, document analysis, automation)
 
 
 Work closely with
 
 investment professionals, research teams, and data engineers
 
 to translate business needs into functional AI solutions
 
 
 Develop and integrate
 
 data pipelines, APIs, and analytical models
 
 to support rapid experimentation
 
 
 Leverage tools such as
 
 Jupyter, Pandas, NumPy, LangChain, and cloud AI services (AWS/Azure/OpenAI)
 
 
 
 Perform
 
 data exploration, feature engineering, and model validation
 
 on financial datasets
 
 
 Iterate quickly on prototypes, incorporating feedback to refine models and outputs
 
 
 Ensure solutions consider
 
 data security, governance, and compliance
 
 within a financial services environment
 
 
 
 Required Qualifications
 
 
 
 10+ years of experience in
 
 Python development
 
 with strong hands-on coding ability
 
 
 Experience building
 
 AI/ML or LLM-based applications and prototypes
 
 
 
 Exposure to
 
 financial services, asset management, trading, or investment research
 
 
 
 Strong experience with
 
 data analysis libraries
 
 (Pandas, NumPy) and working with structured/unstructured data
 
 
 Familiarity with
 
 APIs, microservices, and cloud platforms (AWS, Azure, or GCP)
 
 
 
 Ability to work in a
 
 fast-paced, iterative environment
 
 with direct interaction with business stakeholders
 
 
 
 Preferred Qualifications
 
 
 
 Experience with
 
 LLM frameworks
 
 (LangChain, RAG architectures, vector databases)
 
 
 Knowledge of
 
 financial data sets, market data, or portfolio analytics
 
 
 
 Experience prototyping tools for
 
 quant research, credit analysis, or trading workflows
 
 
 
 Familiarity with
 
 Snowflake, Databricks, or modern data platforms
 
 
 
 
 What Success Looks Like
 
 
 
 Rapid delivery of
 
 high-impact AI prototypes
 
 that demonstrate clear business value
 
 
 Strong collaboration with front-office teams to
 
 solve real investment and research problems
 
 
 
 Ability to evolve prototypes into scalable solutions in partnership with engineering teams
</div>

Python Developer/AI Engineer

Prolific

<div>
 
 AI Trainer &ndash; Machine Learning Specialists
 
 
 
 
 About Prolific
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 The role
 
 
 
 We&rsquo;re looking for
 
 AI Trainer &ndash; Machine Learning Specialists
 
 to help train and evaluate cutting-edge AI models using real ML expertise. If you have the necessary experience, we&rsquo;ll send you a quick
 
 10- to 15-minute test
 
 to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to
 
 $150/hr per AI task completed
 
 . You must be prepared to complete paid tasks that require
 
 one hour of uninterrupted work
 
 , though many are shorter.
 
 
 What you&rsquo;ll bring
 
 
 <ul>
 <li>
 AI Training task skills and verifiable professional experience as a Machine Learning Specialist (e.g., ML engineer, data scientist, applied scientist, research engineer)
 </li>
 <li>
 A willingness to take our skills verification test to assess your suitability for our participant pool
 </li>
 <li>
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 </li>
 <li>
 A reliable and fast internet connection and access to a computer
 </li>
 <li>
 A willingness to self-declare your earnings, as our participants are self-employed
 </li>
 <li>
 A Paypal account to receive payment from our clients
 
 
 </li>
 </ul>
 
 What you&rsquo;ll be doing in the role
 
 
 
 <ul>
 <li>
 Completing AI training tasks such as analyzing, editing, and writing annotations (including technical reasoning and structured evaluation)
 </li>
 <li>
 Judging the performance of AI in performing ML-relevant tasks (e.g., model/experiment critique, data leakage detection, metrics interpretation, debugging approach, methodology review)
 </li>
 <li>
 Improving cutting-edge AI models by providing expert feedback on correctness, robustness, clarity, and technical depth
 
 
 </li>
 </ul>
 
 Key Technologies
 
 
 
 <ul>
 <li>
 General AI Training
 </li>
 <li>
 Model Evaluation and Evals
 </li>
 <li>
 Trust and Safety
 </li>
 <li>
 Red Teaming
 </li>
 <li>
 Quality Analytics
 </li>
 <li>
 Data/ML Concepts (e.g., supervised learning, deep learning, NLP, CV, statistics, experimentation)
 
 
 </li>
 </ul>
 
 Why Prolific is a great platform to join as a Participant
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future using professional machine learning expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breath and the best of humanity.
 
 
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.
</div>

AI Training - Machine Learning Specialist (EST)

Kairon Health

<div><h1 class="jobSectionHeader">About Kairon Health</h1>
Kairon is the execution layer for healthcare. We turn fragmented claims and clinical data into actionable workflows that help ACOs and health networks actually capture their shared savings &mdash; not just measure them after the fact.
We&rsquo;re a seed-stage team of &lt;10, working with real customers managing real patient populations. Our platform spans practice intelligence, care operations, patient activation, and performance analytics. We&rsquo;re AI-native &mdash; not as a buzzword, but because our team builds with Claude, automated transcription, and intelligent workflows as core infrastructure, not bolt-on features.
We&rsquo;re at the stage where our early customers love the product and we need to make onboarding, support, and ongoing operations repeatable without losing the high-touch quality that got us here.<h1 class="jobSectionHeader">
Position Overview</h1>
We&rsquo;re seeking a Senior Product Engineer, Data Applications to own the product layer where data meets decision-making. You&rsquo;ll build the data-powered applications that surface intelligence directly to users &mdash; from the Performance App and ACO-in-a-Box tooling to interactive reporting, scorecards, and next-generation analytics experiences.
This is a full-stack, product-oriented engineering role. You&rsquo;ll design and implement end-to-end solutions (data models, APIs, and UI components) that bring Kairon&rsquo;s insights to life for practice leaders. You&rsquo;ll work closely with engineering leadership, product, and analytics teams to transform complex healthcare data into intuitive, high-impact tools.
You&rsquo;ll thrive here if you&rsquo;re as excited about what you build as why you&rsquo;re building it: an engineer who understands product trade-offs, can shape features from user requirements, and enjoys turning messy data into meaningful, elegant applications.<h1 class="jobSectionHeader">
Key Responsibilities</h1><ul><li>
Own the data-to-application layer: Design, build, and maintain data-driven applications such as performance dashboards, scorecards, and analytic workbenches.</li><li>
Architect end-to-end features: Connect backend models, APIs, and frontend components to deliver interactive insights within the Kairon platform.</li><li>
Collaborate with product and analytics: Translate user needs and clinical/financial metrics into intuitive visualizations and actionable interfaces.</li><li>
Advance in-app intelligence: Integrate data pipelines, LLM insights, and healthcare analytics into user-facing modules (Performance App, ACO-in-a-Box, CRM, and others).</li><li>
Uphold scalability and quality: Design for maintainability, reusability, and performance; implement tests and observability to ensure reliability.</li><li>
Contribute to design &amp; UX: Work with designers to create cohesive, user-friendly experiences that communicate complex data clearly.</li><li>
Champion engineering excellence: Establish best practices, documentation, and component libraries for future applications.</li><li>
Leverage modern AI-assisted tooling: Use LLMs to accelerate development, code review, and refactoring while maintaining rigorous standards.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
6+ years of professional experience building production web applications (frontend + backend).</li><li>
Strong proficiency in Python, Django/DRF, Vue, and SQL; experience with data visualization frameworks and API design.</li><li>
Experience designing or consuming data models and ETL pipelines (e.g., Snowflake, dbt, or similar).</li><li>
Proven ability to translate product requirements into technical architecture and deliver polished, high-impact user experiences.</li><li>
Familiarity with healthcare, analytics, or enterprise SaaS environments.</li><li>
Clear communication and cross-functional collaboration skills; comfort working directly with product and leadership.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Experience in healthcare or value-based care analytics, EHR data, or claims data models.</li><li>
Prior work integrating LLM-driven insights, AI-based summarization, or contextual intelligence into applications.</li><li>
Strong understanding of data visualization principles and UX for analytics products.</li><li>
Background that spans both engineering and product management (technical PM, full-stack data apps, or similar hybrid roles).</li><li>
Previous experience in an early-stage or high-growth startup environment.</li></ul><h1 class="jobSectionHeader">
Why This Role</h1><ul><li>
Impact. You&rsquo;re not maintaining someone else&rsquo;s machine. You&rsquo;re building customer operations from the ground up at a company where the work directly affects whether patients get better care.</li><li>
Growth. This role has a clear trajectory. Depending on your strengths and interests, this becomes Head of Customer Success, Director of Implementations, or a Product leadership role as we scale. You&rsquo;ll have the context and relationships to grow into whatever the company needs most.</li><li>
Stage. We&rsquo;re past the &ldquo;will this work?&rdquo; phase &mdash; customers are live and getting value. We&rsquo;re in the &ldquo;how do we do this 10x without breaking?&rdquo; phase. That&rsquo;s the most interesting operational puzzle in a startup.</li><li>
Equity. You&rsquo;ll have meaningful ownership as one of our first 10 hires, with a real seat at the table.</li></ul>
Diversity and inclusion are core to our culture. If you are a member of an underrepresented group in tech, we strongly encourage you to apply.
Compensation Range: $170K - $190K</div>

Product Engineer, Data

ALICE + OLIVIA

<div>
 
 Location: New York, NY or Secaucus, NJ (Hybrid)
 
 
 Decision Science Engineer (Applied Data Scientist)
 
 
 
 
 
 
 POSITION SUMMARY:
 
 
 
 ALICE + OLIVIA is hiring a Decision Science Engineer to build, operationalize, and own predictive models that improve decision making across Planning, Merchandising/Buying, Customer 360, and Inventory Management. Working primarily within Palantir Foundry as the core analytics and deployment platform, this role bridges data science and platform engineering, translating real-world commercial constraints including seasonality, product lifecycle, allocations, replenishment, promotions/markdowns, and customer behavior into practical, production-grade, human-in-the-loop models.
 
 
 
 
 
 This is a highly cross-functional role with direct, ongoing exposure to business stakeholders and end users, from planners and buyers who consume and act on model outputs, to the teams working within Foundry Workshop applications day-to-day. Understanding how outputs are used in real workflows, and staying close to the people using them, is central to how this role operates. Sitting within the IT organization and serving the full business including DTC, wholesale, planning, and supply chain, this position carries direct visibility to executive business stakeholders. This role is focused on applied data science, decision-support modeling, and model operationalization, not reporting or core data engineering, while partnering closely with Engineering, BI, and the broader Enterprise Applications team.
 
 
 
 
 
 
 RESPONSIBILITIES:
 
 
 <ul>
 <li>
 Design, build, and maintain predictive and statistical models supporting retail planning, buying, inventory, and demand forecasting.
 </li>
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 Operationalize models within Palantir Foundry using Code Workbook and Code Repository, working against Snowflake as the primary data source and ensuring outputs are production-grade and maintainable.
 </li>
 <li>
 Own and evolve analytics logic and assumptions embedded in planning and buying workflows.
 </li>
 <li>
 Partner with Planning, Buying, Merchandising, and DTC teams to translate business needs into model-driven insights, maintaining direct, ongoing relationships with the stakeholders and end users consuming model outputs.
 </li>
 <li>
 Collaborate with the Enterprise Applications team on Workshop app development to ensure model outputs are surfaced effectively in business-facing Foundry applications.
 </li>
 <li>
 Build models for customer segmentation, CLV, retention/churn, propensity, and campaign targeting (Customer 360).
 </li>
 <li>
 Collaborate with Engineering, who owns data pipelines and Snowflake ingestion, to ensure model inputs are reliable, well-governed, and fit for purpose without owning the underlying data infrastructure.
 </li>
 <li>
 Support human-in-the-loop workflows where planners and buyers can interrogate, override, or adjust model outputs in real time.
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 <li>
 Validate model outputs against business reality and historical performance, closing the loop directly with end users on model accuracy and relevance.
 </li>
 <li>
 Document methodologies and assumptions to support long-term ownership and institutional knowledge.
 </li>
 </ul>
 
 
 
 
 
 QUALIFICATIONS:
 
 
 <ul>
 <li>
 4 to 8+ years of experience in data science, applied analytics, or predictive modeling.
 </li>
 <li>
 Strong experience building predictive or statistical models including forecasting, optimization, regression, and classification.
 </li>
 <li>
 Proficiency in Python for data analysis, modeling, and production-grade code.
 </li>
 <li>
 Strong SQL and hands-on experience with Snowflake or equivalent cloud data warehouse.
 </li>
 <li>
 Experience with Palantir Foundry strongly preferred, including familiarity with the Foundry Ontology layer, analytics and modeling tooling (Code Workbook, Code Repository), and how model outputs are surfaced through business-facing applications. Candidates who can reason within and contribute to an existing Ontology, and who understand how the semantic data layer connects to model design, will be prioritized.
 </li>
 <li>
 Familiarity with experiment design and causal inference.
 </li>
 <li>
 Experience with time-series forecasting at scale.
 </li>
 <li>
 Retail domain experience strongly preferred, including familiarity with demand vs net sales, sell-through, markdowns, planning vs buying workflows, seasons, price groups, and store vs e-commerce dynamics.
 </li>
 <li>
 Experience working with messy, real-world data and designing models that support business judgment.
 </li>
 <li>
 Ability to reason about semantic or ontology-based data models.
 </li>
 <li>
 Strong communication and relationship skills, comfortable working directly with planners, buyers, and business stakeholders, and able to translate model outputs into decisions, not just insights.
 </li>
 <li>
 Long-term ownership mindset for maintaining and evolving models over time.
 </li>
 <li>
 Hands-on experience building or contributing to Palantir Foundry Workshop applications.
 </li>
 <li>
 Background in wholesale or multi-channel retail, including familiarity with the operational differences between DTC, wholesale, and brick-and-mortar planning cycles.
 </li>
 <li>
 Exposure to agent-based or AI-assisted analytics workflows.
 </li>
 <li>
 Experience working within a formal data governance or steerco-driven prioritization structure.
 </li>
 <li>
 Familiarity with Snowflake-native development patterns including dbt, Snowpark, or similar.
 </li>
 </ul>
 
 
 
 
 
 ADDITIONAL INFORMATION:
 
 
 
 This role sits within the IT organization, reporting to the VP of Information Technology, and operates across the full business including Planning, Merchandising/Buying, DTC, and Supply Chain. Engineering owns ETL, data pipelines, and Snowflake ingestion. BI owns reporting and dashboards. This role owns predictive modeling, decision-support analytics, and model operationalization within Palantir Foundry. Work is prioritized through a cross-functional steering committee with direct business stakeholder representation, ensuring this role has structured visibility into commercial priorities and executive-level exposure from day one.
 
 
 
 
 
 ALICE + OLIVIA is at an inflection point in how it uses data to make decisions. This role is central to that transformation, building the analytics capability that connects our Palantir Foundry investment to real commercial outcomes across every part of the business. This is not a role that maintains existing infrastructure or produces reports. It is a greenfield opportunity to own a strategic function, work directly with the teams making decisions, and build something that compounds in value over time. For the right person, it is a rare combination of technical depth, business proximity, and organizational support.
 
 
 
 
 
 $150,000 -175,000 base salary (This range represents the low and high end of the anticipated base salary range for this NY OR NJ - based position. The base salary will depend on numerous factors such as: experience and qualifications for the role, experience level, skillset, and balancing internal equity relative to other A+O employees.)
 
</div>

Data Scientist

Traversal

<div><h3 class="jobSectionHeader">About Traversal</h3>
Traversal is the AI Site Reliability Engineer (SRE) for the enterprise&mdash;already trusted by some of the largest companies in the world to troubleshoot, remediate, and even prevent the most complex production incidents. Our mission is to free engineers from endless firefighting and enable them to focus on creative, high-impact work.
Our roots remain deeply embedded in AI research, and we&rsquo;re channeling that scientific rigor and creativity into building the premier AI agent lab for the enterprise. Hence, what we&rsquo;re proudest of is assembling the most talented yet nicest group of individuals, including researchers from MIT, Harvard, and Berkeley, to world-class engineers from industry: Citadel Securities, Cockroach Labs, Datadog, DE Shaw, ServiceNow, Glean, Perplexity, Pinecone, and more, to take on one of the hardest problems for AI to solve. Without the entire team, none of this would be possible.<h3 class="jobSectionHeader">
The Role</h3>
As a Product Engineer at Traversal, you&rsquo;ll play a key role in designing and building core features powered by our AI site reliability engineer. From the user interface to the backend and infrastructure, you&rsquo;ll develop product components to enable real-time incident detection, root cause analysis, and automated remediation in some of the most complex production environments. This role will focus on the ability to work across the full pipeline of our product, and someone who can have a strong product sense while also being comfortable working around AI and data processing infrastructure will be the best fit.<h3 class="jobSectionHeader">
Responsibilities</h3><ul><li>
Product Impact: Translate AI-powered insights into user-friendly features that empower engineers and reduce cognitive load.</li><li>
User Experience: Innovate and drive the evolution of UX/UI design, rapidly iterating based on user feedback to improve overall usability.</li><li>
Agent Development: Build AI agents with a mind for user-experience and capabilities like long-horizon work, proactiveness, readability, and evidence citation.</li><li>
API Development: Design and implement high-performance APIs to enable seamless communication between backend systems and frontend interfaces.</li><li>
Data Management: Ensure efficient data storage, retrieval, and processing, leveraging technologies like PostgreSQL, Redis, or others.</li><li>
AI Integration: Collaborate with AI engineers/researchers to integrate AI-driven insights and solutions into backend systems, and take ownership of API authentication and authorization frameworks.</li><li>
Data Visualization: Develop intuitive interfaces for presenting and interacting with complex time-series and topological data.</li></ul><h3 class="jobSectionHeader">
Requirements</h3><ul><li>
4+ years of software engineering experience, with a strong focus on full-stack systems.</li><li>
Proven ability to lead in fast-paced startup environments, with limited resources, shifting priorities, and minimal structure.</li><li>
Strong experience with Python and web frameworks such as FastAPI.</li><li>
Hands-on experience with React, TypeScript, Next.js, and TailwindCSS to build fast, responsive, and maintainable frontends.</li><li>
Experience deploying applications on AWS, working with ECS or Kubernetes, Postgres for data storage, and S3 for large-scale object storage.</li><li>
Note: You don&rsquo;t need to meet every single requirement. If you have deep experience in a subset of these areas, we encourage you to apply.</li></ul><h3 class="jobSectionHeader">
Nice to Have</h3><ul><li>
Familiarity with Python-based ecosystems is a plus.</li><li>
Experience working with Agentic AI systems or in the observability domain.</li><li>
Background in large-scale, complex, data-driven applications.</li><li>
Familiarity with building AI or LLM-powered products.</li></ul><h3 class="jobSectionHeader">
Compensation</h3>
We offer competitive compensation, startup equity, health insurance, and additional benefits. The U.S. base salary range for this full-time, in-person role in New York is $150,000&ndash;$300,000, plus equity and benefits. Our salary ranges are based on location, level, and role. Individual compensation is determined by experience, skills, and job-related knowledge.<h3 class="jobSectionHeader">
Why You Should Join Us</h3>
We&rsquo;ll make sure you&rsquo;re fully supported with health insurance, a great tech setup, flexible time off, and plenty of in-office snacks. We offer competitive salary and equity packages, and take thoughtful consideration with every hire on our small, high-impact team.
Traversal is fully in-office, 5 days a week, based in New York near Madison Square Park. We have a collaborative, hard-working culture and are energized by building the future of AI-powered software maintenance.
Working here means owning meaningful parts of the product, having the flexibility to move fast, and learning constantly. This is a place to grow your career, make a real impact, and help define a new category of infrastructure software.</div>

Product Engineer

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