About Triomics:

nTriomics helps oncology organizations scale clinical research and high-quality data creation without scaling headcount. Our AI platform - powered by OncoLLM™- automates the operational work behind trial screening, eligibility interpretation, and oncology data abstraction across Prism (trial matching), Harmony (registry + RWE curation), and Symphony (clinician copilot). Built for real-world hospital workflows, Triomics integrates with EHRs and CTMS systems and is deployed with leading academic cancer centers to improve speed, consistency, and audit-ready clinical accuracy.

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nPart of the Oncology Clinical Team, this role focuses on training, validating, and continuously improving AI-driven oncology data extraction and trial-matching systems. This role collaborates closely with NLP, product, and operations teams to refine model outputs, build oncology data dictionaries, optimize abstraction logic, and ensure clinical accuracy across oncology workflows.

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nPosition Summary:

nThis role works at the intersection of oncology and artificial intelligence. The role is responsible for evaluating and refining AI-generated outputs from electronic health records and clinical databases to ensure accuracy, consistency, and protocol alignment. Responsibilities include validating model-driven eligibility determinations, tuning oncology data dictionaries, improving abstraction logic, and supporting AI model performance across solid and hematologic malignancies.

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nKey Responsibilities:

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- Review oncology patient cases for clinical trial eligibility using inclusion/exclusion criteria by validating and refining AI-assisted eligibility determinations.
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- Provide structured feedback to improve AI model performance on inclusion/exclusion logic.
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- Translate complex protocol requirements into structured, model-readable logic to enhance automated trial build and screening process.
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- Review and refine AI-extracted diagnostic, pathology, imaging,



and treatment data for accuracy and protocol compliance.
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- Collaborate with NLP and product teams to tune oncology-specific data dictionaries and abstraction frameworks.
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- Define and improve abstraction rules to enhance automated clinical data structuring.
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- Serve as an oncology subject-matter expert to guide model optimization across solid and hematologic malignancies.
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- Identify systematic error patterns in AI outputs and propose workflow or model-level improvements.
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- Conduct second-level and quality-control reviews to benchmark AI performance.
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- Contribute to SOP development for AI-assisted abstraction workflows.
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nQualification:

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- Strong oncology domain expertise across diagnosis, staging, grading, and systemic therapies.
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- Experience reviewing medical records for oncology clinical trials.
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- Comfort working with AI-assisted workflows and structured data systems.
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- Certification in Clinical Research or Clinical Data Management preferred.
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nEducation:

nB.Sc (Nursing), BDS, BAMS, BHMS, MDS, BPharm, MPharm

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nSkills and Abilities:

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- Excellent written and verbal communication skills; able to collaborate with internal and external stakeholders in a fast-paced environment.
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- Sound judgment in abstracting medical data, with the ability to work independently and to escalate or seek input when appropriate.
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- High adaptability to changing assignments, project requirements, training schedules, and occasionally suboptimal tools or databases.
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- Proficient with Microsoft Office (Word, Excel, Outlook, PowerPoint); able to create,



maintain, and share professional documents and reports.
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nWhy Join us ?

n1. We are revolutionizing a unique industry that has the potential to impact and benefit patients

nfrom all over the world - you can create impact at scale.

n2. We have had company - sponsored workations in Bali, Sri Lanka, and Manali and take pride in our hard-working yet super fun culture .

n3. We are working on a few of the most challenging problems in a highly regulated industry which provides you an opportunity to solve some of the most interesting things.

n4. You will get a chance to work with experts from multiple industries and the best in the industry Compensation.

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nThis role demands strong expertise in:

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- Histological classification of solid malignancies - mainly breast, lung, GI, GU and Gynecological cancers.
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- Hematologic cancers (leukemia, lymphoma, myeloma) - Types, staging, diagnosis and treatment.
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- Biomarkers/tumor markers.
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- TNM classification.
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- Types of cancer therapy in detail.
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- Mechanism of action of chemotherapy.
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nWhy Join Us?

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- Impact at scale: The quality you ensure directly affects AI workflows that accelerate cancer research and improve patient outcomes globally
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- Cutting-edge problems: Test complex, data-intensive systems at the intersection of AI, healthcare, and scale
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- World-class team: Collaborate with top talent across AI, engineering, and product with best-in-industry compensation
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- Culture that ships: Fast-paced, ownership-driven environment with company-sponsored workations (Bali, Sri Lanka, Goa, and more)
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nPerks & Advantages

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- Lunch provided at the office — one less daily decision
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- Flexible working hours — we care about output, not clock-ins
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- Comprehensive health insurance for you and your family
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- Zomato meal benefits for early starts and late nights
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📌 Clinical Data Abstractor (Bengaluru)
🏢 Triomics
📍 Bengaluru