I operate at the intersection of AI, human genetics, and commercial strategy. At Genomics, I help pharmaceutical and biotech organizations bring large-scale human genetics into earlier, more confident R&D decision-making—through a combination of advanced analytics, AI-enabled tooling, and strategic consulting support.

My work centers on partnering with senior R&D, statistical genetics, and strategy leaders to operationalize genetics across the pipeline: accelerating target discovery, strengthening validation, improving translational confidence, and identifying patient populations more likely to respond to therapy.

Over the past 20 years, I’ve:

•	Built, led, and mentored high-performing sales teams in AI and SaaS.
•	Managed global accounts and developed go-to-market strategies that drive adoption.
•	Closed multi-million-dollar enterprise engagements and partnerships across R&D industries 
•	Negotiated strategic agreements that expand revenue and accelerate growth.

I’m also the author of Mastering AI Sales: Essential Knowledge for B2B Professionals, a practical playbook that equips founders, consultants, and sales leaders with frameworks to win complex AI sales.
👆 Now available – click the link in my profile header to get your copy.

Specialties

•	AI-Enabled Human Genetics / Genomics Commercial Strategy
•	Building & Scaling Sales Teams
•	Enterprise AI Sales & Stakeholder Management
•	Go-to-Market Strategy (Consulting + Product Hybrid Models)
•	Strategic Partnerships & Revenue Expansion
•	Cross-Functional Leadership & Commercial Alignment

Let’s connect if you’re scaling AI solutions, leading enterprise transformations, or looking to accelerate sales impact in complex markets.

David Walker

Early JPM takeaways…

• Causal genetics is firmly front and center, increasingly used to de-risk target identification and validate programs earlier in development.
• Patient stratification is no longer optional. Leaders are entering the clinic with greater emphasis on clear responder hypotheses and stronger supporting evidence.
• AI is maturing quickly. Fewer proof-of-concept discussions, more concrete examples of measurable impact across R&D.
• Funding sentiment appears cautiously improved, particularly for companies with differentiated science and disciplined, evidence-led strategies.

The Genomics leadership team is here all week and we’d be happy to connect and compare notes.

#jpm2026 #Genomics

VP of Client Service | Leading Enterprise AI Partnerships | Team Builder | Author of Mastering AI Sales | MBA, MSc.

JPM was an outstanding experience. The energy, quality of conversations, and level of innovation throughout the week were exceptional.

We were delighted to host a Genomics reception, where we shared how Mystra, our AI enabled platform, enables teams to apply human genetics more effectively to R&D decision-making. The depth of engagement reinforced just how central genetics has become to smarter target selection and clinical decisions.

A few key takeaways stood out for me…

1. Platforms must change decisions
AI creates value only when it changes decisions e.g. which targets advance, which programs stop earlier, and which patients enter trials. The strongest platforms enable fewer, higher-confidence bets.

2. Data advantage ≠ more data
The ultimate advantage is signal, not scale. Rare disease cohorts, longitudinal datasets, and multi-omics data with clinical context enable better questions to be asked and reduce false confidence.

3. Causal genetics is becoming foundational
Human genetics is increasingly being used to improve probability of success, de-risk programs earlier, enable patient stratification, and support smarter trial design.

The next phase of R&D won’t be defined by who moves fastest, but by who makes the best decisions earliest, using well-curated data, causal evidence, and AI together.

#JPM26 #Genetics #TargetValidation #PatientStratification #DrugDevelopment

I'll be heading to JPM next week. If you’ll be there too, drop me a message, it’d be great to connect in person.

🎉 We're starting the year in San Francisco! Our team will be arriving later this week for the J.P. Morgan Healthcare Conference.

We are looking forward to a busy few days connecting with colleagues from the Department for Business and Trade, and senior leaders across pharma and biotech.

From Saturday, January 10th, our CEO and Co-Founder, Professor Sir Peter Donnelly, President David Thornton, VP of Client Service David Walker, and Director of Communications Zuzanna Grzeskiewicz will be on the ground in San Francisco, ready to connect.

If you're going to be in San Francisco next week and would like to meet with our team, click here: https://lnkd.in/eT9qFMyy

See you soon! 🚀 

#JPM2026 #JPMWeek #techbio #genomics #JPM #pharma #biotech #healthcare #SanFran

Great to see the Genomics team out in force at #FOG2026 
If you’re at FOG, make sure you stop by by Booth #77 to say hello and check out the Mystra D&D Quest, a fun, hands-on way to experience how we support drug target discovery and development through human genetics and multi-omics.   Plus Dirk Paul, Head of Development, talking about: “The Genome and Beyond: Advancing Drug Discovery and Development” Today 12:00–12:30 | Multi-Omics Stage
Have a great show, team 👋
#DrugDiscovery #MultiOmics #Genomics #DrugDevelopment #FOG2026 #FrontLineGenomics

Day 1 at #FOG2026 is here 🚀 

You can find us at Booth #77 - come say hello to the team and try our iconic Mystra D&D Quest 🧙 - an interactive challenge that gives you a hands-on experience with our drug target discovery and development platform! 

🎤 Today | 12:00 - 12:30 | Multi-Omics stage
Join Dirk Paul, Head of Development, for "The Genome and Beyond: Advancing Drug Discovery and Development"
What to expect:
💡 Insights into Genomics' genotype-phenotype platform & analytical pipelines
🧬  A deep dive into how multi-omics integration drives target identification & data-driven patient stratification
🌍  Real-world case case studies showcasing risk prediction and pharmacomimetic approaches in action

See you on the floor 👋 

#drugdiscovery #MultiOmics #Genomics #DrugDevelopment Front Line Genomics

Quantori

- Led 8-person cross-functional team in developing RAG-powered candidate matching system (Azure AI infrastructure)
- Architected document processing pipeline handling 500+ CVs/day using LangChain orchestration and OpenAI embeddings
- Mentored 3 developers in RAG implementation best practices while coordinating with QA lead to build AI testing framework from scratch
- Team Lead responsibilities: Technical roadmap planning, sprint task allocation, and AI ethics compliance verification
- Engineered hybrid ranking system combining GPT-4 embeddings with semantic reranking models (faithfulness to Responsible AI principles)

Key Technologies: Azure AI Services, OpenAI GPT-4, LangChain, Python, RAG Architecture, CI/CD Pipelines, Responsible AI

Senior Software Engineer

# Building a pipeline file processing tool aims to automate generation of picklist instructions for the Acoustic Liquid Handlers

- Contributed to building a pipeline file processing tool to automate picklist instructions generation for the Acoustic Liquid Handlers.
- Supported and developed complex Python transforms on the Palantir Foundry platform, enhancing data analysis capabilities and increasing efficiency.
- Increased test coverage from 70% to 95%, ensuring improved quality and stability of pipeline systems.
- Doubled the number of pipeline modes, resulting in increased speed of customer's experimental work.
- Communicated effectively with customers to clarify business requirements, enhancing customer satisfaction and retention.
- Provided continuous technical support for a customer-critical application, improving customer satisfaction and loyalty.

Environment: Palantir Foundry, Python, Spark, pandas, pytest, openpyxl



# Developed the backend of a Laboratory Information Management System.

-I mplemented robust endpoints utilizing FastAPI and GraphQL, resulting in improved API performance and efficiency.
- Built powerful data models using strawberry, increasing scalability and flexibility of data storage.
- Streamlined container building instructions, improving deployment speed and efficiency.

Environment: Python, FastAPI, GraphQL, Docker, Bitbucket, strawberry, pytest



# Creating scripts for parsing files on the Dotmatics platform

- Successfully developed and implemented scripts for parsing various file formats on the Dotmatics platform, receiving positive feedback on data processing accuracy and efficiency.
- Tested, debugged, and integrated the scripts into the project workflow, resulting in a streamlined and automated data processing pipeline.
- Continuously updated and improved the scripts, providing valuable technical expertise and delivering high-quality code on time.

Environment: Dotmatics, Python2.5, git

Software Engineer

# Discovering concealed connections among illnesses through the examination of EHR with the aid of machine learning techniques

- Discovered concealed connections among illnesses through examination of Electronic Health Records (EHR) using machine learning techniques.
- Developed a comprehensive data collection and preparation pipeline, improving efficiency and accuracy of data analysis.
- Conducted cutting-edge data science experiments, analyzing and reporting results to drive business decisions and improve performance.
- Implemented a new data visualization pipeline to evaluate model performance and identify areas for improvement.
- Designed and developed unit tests to ensure reliability and accuracy of data analysis processes.

Environment: Python, AWS, JupyterHub, GitLab, Docker, sqlalchemy, pandas, statsmodels, gensim



# Building a pipeline document parsing tool and a full-text search engine for biopharma companies

- Built a pipeline document parsing tool and a full-text search engine for biopharma companies.
- Developed, tested, and debugged software tools to facilitate user experience.
- Improved the scientific NLP engine.
- Created a text scraping and converting tool for extracting data from files of different formats and converting it to .xml format.
- Created an ontology for the NLP engine.

Environment: Python, PostgreSQL, AWS, GitLab, Bitbucket, pytest



# Developing a desktop GUI application for spectra image scientific preprocessing

- Developed a desktop GUI application for spectra image scientific preprocessing.
- Developed the GUI with Qt Designer and the application's back-end components.
- Designed and created test cases and performed manual testing.
- Created an automated scientific image analysis tool.

Environment: Python, PySide2, Qt Designer, NumPy, Matplotlib

Junior Software Engineer

Ioffe Institute

Scientific research in experimental and theoretical physics. Delivering data collection, processing, analysis, and visualization automation tools for a physics and technology research institute

Tasks and Achievements: 
Enabled automated experiment data collection
Developed a data processing tool with Python
Performed and conducted a multivariate statistical analysis of experimental data 
Developed an automated reporting tool
Authored multiple publications and conference proceeding

Scientific Researcher

Experienced Senior Software Engineer and AI Team Lead with a proven track record of designing and deploying enterprise-scale AI solutions. I specialize in bridging complex technical challenges with business outcomes, LLMs and RAG to solve real-world problems.

With a background in physics and scientific research, I bring a data-driven, analytical mindset to software development. Over the past 3+ years, I’ve led teams to build innovative tools for biotech, healthcare, and lab automation, including AI-driven candidate matching systems that improve hiring efficiency.

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