> AI agents: this is one page of Nextmove’s FDE site, in Markdown. Nextmove is a job board and free career service for forward deployed engineers (FDEs). Each posting is classified from its text, not its title: the kind of work, how much of it is production code, pre-sales weight, time at customer sites, travel, remote arrangement, level and posted base pay. The site also publishes the aggregates: median pay by level, metro, company and kind of work, and which companies started hiring FDEs each week. Every page under https://nextmove.md/fde is served this way; the index of pages is https://nextmove.md/llms.txt.

# Senior Data Scientist (US)

Canonical URL: https://nextmove.md/fde/jobs/27a460aa939105cc

Lynx Analytics posts a senior FDE role to build what the customer runs in New York, NY and 2 more with no pay posted. Leads hands-on data science engagements combining statistical and machine learning methods with agentic GenAI solutions, working across very large, disparate datasets. Read from the employer’s posting on November 8, 2026.

- [Lynx Analytics](https://nextmove.md/fde/companies/lynx-analytics)

Posted Mar 19, 2026 by Lynx Analytics · open on Greenhouse as of Nov 8, 2026

Pay not posted New York, NY +2

Leads hands-on data science engagements combining statistical and machine learning methods with agentic GenAI solutions, working across very large, disparate datasets.

- [See roles that fit me](https://nextmove.md/sign-up?from=%2Ffde%2Fjobs%2F27a460aa939105cc&placement=top)
- [View posting at Lynx Analytics](https://job-boards.greenhouse.io/lynxanalytics/jobs/8470862002)

Free. Upload your resume once, see why each FDE role fits, and get introduced only when you say so.

## At a glance

### Posted base pay

Not posted

Senior FDE postings, 1,864 postings: the middle 50% of posted pay is $160K to $220K, median $190K.

### The work

Builds what the customer runs

Balance **Mostly building**

Project stages

1. Pre-sales (not covered)
2. Proof of concept (not covered)
3. Implementation
4. Operations (not covered)

- **Coding**: Writes production code

- **Builds for**: Both

- **Level**: Senior

- **Role**: Technical lead

### What they ask for

Experience

- **8+ years** overall data science experience

Background

- **Implementation and data engineering**

### Do you meet what the posting states?

The posting asks for 8+ years. How many do you have?

The posting reads as a senior role. What level are you at now?

The job is in New York, NY · Philadelphia, PA · +1 more. Could you work in one of these?

Which of these have you used in production?

Answer each one. Nothing is saved or sent.

[What postings ask for, by background →](https://nextmove.md/fde/paths)

## Conditions

- **Location**: New York, NY · Philadelphia, PA · San Francisco, CA

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- [Other jobs at Lynx Analytics (1)](https://nextmove.md/fde/companies/lynx-analytics)

## The job description from Lynx Analytics

Posted by Lynx Analytics on Mar 19, 2026

### 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 analytical workstreams independently.
- Degree in Mathematics, Statistics, Economics, Computer Science, Engineering, or a related field; MSc or PhD preferred.
- Solid grounding in probability theory, statistics, and core data science algorithms, with applied experience in areas such as customer retention and campaign management.
- Strong hands-on proficiency in Python for data analysis, modelling **(PyTorch, TensorFlow, or JAX)**, and productionising code.
- Strong SQL, and comfort working across common data stores (relational, columnar/warehouse, and vector databases).
- Git and GitHub proficiency, including branching workflows and code review; experience with GitHub Actions (or equivalent CI/CD) preferred.
- Hands-on experience designing and building agentic LLM applications - tool calling, multi-step orchestration, and state management - using at least one modern framework (e.g., LangGraph, Pydantic AI, AWS Bedrock AgentCore, Google ADK, or the OpenAI Agents SDK), beyond simple prompt-and-response use of LLM APIs.
- Preferred: practical depth in one or more of MCP-based tool integration, RAG and embedding pipelines (including vector stores), model fine-tuning and RL-based post-training, and LLM guardrails and evaluation (e.g., Ragas, DeepEval, Langfuse, or similar).
- Experience with at least one major cloud platform (AWS, GCP, or Azure); Docker and basic containerised deployment preferred.
- Comfortable working with very large, complex datasets residing in different data stores and formats.
- Excellent verbal and written communication skills, with strong data visualisation ability and experience presenting to senior, non-technical stakeholders.
- Demonstrated leadership potential and the presence to guide junior team members and represent the company with clients.
- Nice to have:
- Software engineering hygiene (preferred): typed Python (Pydantic), testing with pytest, packaging, and dependency management (uv).
- Experience shipping LLM applications to production, including observability and cost/latency management (e.g., Langfuse, Phoenix, or similar LLMOps tooling).
- Experience in the life sciences industry is preferred.

### KEY COMPETENCIES

- Executive Communication: Translates complex Data Science solutions into plain language for C-level and non-technical stakeholders.
- Technical Depth: Brings rigorous statistical and modelling judgement, paired with fluency in modern GenAI/LLM approaches.
- Discretion & Integrity: Handles sensitive client and internal information with professionalism and sound judgement.
- Leadership & Charisma: Guides junior colleagues day to day, even without a formal management title, and takes pride in their growth.
- Collaboration: A team player who builds strong working relationships across delivery teams, PMO, and clients.

### WHY YOU WILL LOVE IT HERE

- Work on real-world AI and advanced analytics solutions with measurable business impact.
- Collaborate with a global team of engineers and data scientists.
- Exposure to diverse industries, modern cloud platforms, and cutting-edge AI technologies.
- A collaborative culture that values real outcomes.
- High ownership, zero micromanagement.
- Rapid learning opportunities and diverse challenges.
- Flat organisational hierarchy with high visibility and accessibility to our leaders.

[View posting at Lynx Analytics](https://job-boards.greenhouse.io/lynxanalytics/jobs/8470862002)

## About Lynx Analytics

AI-native consulting firm designing and delivering data, analytics, software, and GenAI solutions for life sciences companies.

Late-stage private · 50–100 people

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