John Snow Labs

• Responsible for developing and managing our partners’ ecosystem of advisory, system integrators and technology partners • Acquire, onboard, and enable new partners (resellers, referrals, advisory, system integrators, and technology partners) and manage relationships with existing partners • Identify new targeted partners (acquisition plan) aligns with our goals in our fast paced, startup mentality environment • Develop and execute an impactful go-to-market plan to acquire and activate new partners in our ecosystem • Engage and follow up with new and existing partners to sign-up to the partnership program, support onboarding and execute the sales through the channel partners ecosystem • Drive a consistent growth in sales capacity through the partners’ ecosystem • Coordinate effective communication channel with Partners: including training sessions, webinars, partner program updates, demo videos, product updates together with the marketing and business development team • Execute Monthly and Quarterly Business Reviews with key partners • Report on partners’ acquisition and business status • Aggregate pipeline and forecasting engagements and report to the leadership • Create top accounts blueprints and deals closing plans • Co-own and help to improve Kore.ai partnership program

• Lead technical onboarding activities for new clients. • Analyze source systems and data architectures. • Design and implement connectors to various data sources, including: EHR systems, FHIR servers, HL7 interfaces, Relational databases, Data warehouses, Cloud storage platforms (S3, Azure Blob, GCS), Flat-file and CSV-based exchanges, APIs and custom integrations • Collaborate with client IT and clinical informatics teams to understand source data structures and workflows. • Define integration strategies and technical specifications. • Map source data into healthcare interoperability standards and common data models. • Support transformation of clinical data into OMOP CDM. • Develop and maintain source-to-target mappings. • Identify and resolve data quality, terminology, and interoperability issues. • Build, test, and maintain ETL/ELT pipelines. • Collaborate with data engineers, data scientists, and machine learning engineers.

Role Description John Snow Labs is seeking a highly skilled and motivated Data Analyst to contribute to transformative initiatives within the healthcare industry. As a leading healthcare organization, we are committed to leveraging data to improve patient outcomes and streamline healthcare operations. We are seeking a skilled Data Analyst with expertise in converting Electronic Health Records (EHR) to the OMOP Common Data Model (CDM), particularly using Epic EHR systems. As a Data Analyst, you will be responsible for the transformation of healthcare data from Epic EHR into the OMOP CDM format. This role requires keen attention to detail and a strong understanding of healthcare data standards to ensure data integrity and interoperability. - Perform data extraction, transformation, and loading (ETL) of healthcare records from Epic EHR to OMOP CDM. - Collaborate with clinical informaticists and data engineers to ensure accurate mapping and conversion of data. - Validate and test data conversions to maintain high levels of accuracy and consistency. - Troubleshoot and resolve data integration issues as they arise. - Document processes and create comprehensive reports on conversion progress and outcomes. - Hands-on experience with OMOP, FHIR, clinical terminologies, and understanding of the patient journey. - A strong background in healthcare-related fields such as medicine, pharma, bioinformatics, or biostatistics is highly beneficial. - Experience with John Snow Labs’ technology stack, such as Spark NLP or the medical language models, is a plus. Qualifications - A PhD in a relevant field is preferred but not required if exceptional experience is demonstrated. - Proven experience in EHR data management, specifically with Epic EHR systems. - Strong understanding of the OMOP Common Data Model and healthcare data standards. - Proficiency in SQL and experience with data transformation tools. - Excellent analytical and problem-solving skills. - Strong attention to detail and ability to work independently or as part of a team. Requirements - Experience with ETL tools and processes. - Familiarity with regulatory and compliance standards in healthcare data management. - Strong communication skills, both written and verbal. Benefits - A chance to work on cutting-edge problems in healthcare and life sciences, contributing to meaningful projects that impact patient outcomes. - Long-term freelancing contracts with a commitment of at least 30 hours per week. We are seeking individuals, not agencies or teams. - The opportunity to grow your skills and knowledge, working with a team of big data and data science experts in a supportive, collaborative environment.

• Design, develop, and maintain cutting-edge web services and applications. • Architect and implement scalable, efficient, and maintainable full-stack solutions. • Collaborate with cross-functional teams to define, design, and ship new features. • Write clean, high-quality code for both front-end and back-end components. • Optimize application performance and ensure high availability. • Participate in code reviews and contribute to improving our development practices. • Mentor junior developers and provide technical leadership. • Stay up-to-date with emerging trends and technologies in full-stack development. • Troubleshoot, debug, and upgrade existing systems. • Implement security and data protection measures. • Contribute to the continuous improvement of our development processes and tools.

• Adapt LLMs to diverse healthcare use-cases using techniques such as Sparse Fine-Tuning (SFT), Prompt Engineering Fine-Tuning (PEFT), Direct Parameter Optimization (DPO), and Proximal Policy Optimization (PPO). • Optimize LLMs for Retriever-Augmented Generation (RAG) to enhance decision-making and information retrieval capabilities. • Collect, clean, and refine healthcare datasets for training LLMs to ensure high-quality data provisioning. • Convert models into various formats suitable for production environments, ensuring their readiness for real-world application.

• Serve as a subject matter expert (SME) on cancer registry data standards, abstraction workflows, and reporting requirements • Provide structured walkthroughs of the registry lifecycle — from casefinding, abstraction, coding, QA, to submission and feedback • Advise on the interpretation of data dictionaries, staging schemas, and coding logic used across U.S. registries • Help our team understand the daily workflow of registrars, including interaction with EHRs, pathology feeds, and state/federal reporting systems • Review data models, variable mappings, and potential automation use cases for consistency with registry standards • Participate in periodic review meetings (remote) to guide technical and product teams on oncology data conventions • Provide occasional feedback on UI/UX mockups, training materials, or registry-related data capture prototypes

• Full-Cycle Ownership: Manage the entire sales process from initial technical discovery and "talking shop" with Data Science leads to final contract execution • Technical Discovery: Conduct deep-dive discovery calls to understand the customer’s specific data challenges (e.g., patient registries, clinical trial optimization, or de-identification) • Strategic Territory Planning: Build and execute a plan for your assigned territory to exceed quarterly and annual booking targets for subscriptions and services • Stakeholder Management: Orchestrate relationships across the organization, ensuring the technical "champions" stay engaged while the "economic buyers" see the ROI • CRM Discipline: Maintain meticulous records and accurate forecasts within our CRM to ensure transparency across our distributed team