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Senior Associate, Patient Analytics (Breast Cancer)

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What you’ll work on

Full posting

We are hiring a Senior Associate who enjoys working hands-on with real-world data and turning it into answers pharma brand teams can act on.

  • Build breast cancer patient cohorts from claims and EMR data by subtype, stage and biomarker

  • Write and validate logic for line-of-therapy, persistency, adherence and time on therapy

  • Track biomarker testing patterns and find patients tested but not treated, or treated without testing

  • Turn data outputs into charts and slides and present them in client working sessions

  • Build and maintain data pipelines and Tableau dashboards for brand and launch tracking

From the employer’s posting
We are hiring a Senior Associate who enjoys working hands-on with real-world data and turning it into answers pharma brand teams can act on. You will work on breast cancer engagements for US pharma clients, building the cohorts, algorithms and analyses for each client's requirements. Over time you will extend this work to other Oncology, Immunology and Rare disease areas. You will work closely with the engagement Manager and grow into leading workstreams yourself.
Build breast cancer patient cohorts from claims and EMR data
Write and validate the logic behind core metrics: line-of-therapy assignment, regimen grouping, persistency, adherence, time on therapy and source of business.
Track biomarker testing patterns (HER2, ER/PR, PD-L1) and identify patients who are tested but not treated, or treated without testing.
Translate data outputs into clear charts and slides, and present findings in working sessions with client teams.
Build and maintain data pipelines and Tableau dashboards for ongoing brand and launch tracking.

What you’ll bring

All qualifications

Core experience

  • Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Data Science, Engineering, Life Sciences).
  • 3–5 years of experience in US pharma analytics, with most of it spent working directly with patient-level data.
  • Familiarity with oncology coding (ICD-10, NDC, J-codes) and experience with APLD/claims, EMR and lab datasets.
  • Strong SQL and Python/PySpark skills; experience building dashboards in Tableau or similar tools.
Qualification wording
Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Data Science, Engineering, Life Sciences).
3–5 years of experience in US pharma analytics, with most of it spent working directly with patient-level data.
Familiarity with oncology coding (ICD-10, NDC, J-codes) and experience with APLD/claims, EMR and lab datasets.
Strong SQL and Python/PySpark skills; experience building dashboards in Tableau or similar tools.
Apply at KMK Consulting

Posting record

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Status in our records
Live
First seen by us
Oct 19, 202616 days ago
Recorded sightings
18
Last seen by us
Nov 4, 2026

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KMK Consulting is hiring

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  • Python
  • SQL
  • Tableau
  • PySpark
Where the posting names them
- Familiarity with oncology coding (ICD-10, NDC, J-codes) and experience with APLD/claims, EMR and lab datasets. - Strong SQL and Python/PySpark skills; experience building dashboards in Tableau or similar tools. - Good to have: Exposure to other Oncology, Immunology or Rare disease data, or to predictive / machine learning models.
- Translate data outputs into clear charts and slides, and present findings in working sessions with client teams. - Build and maintain data pipelines and Tableau dashboards for ongoing brand and launch tracking. - Check your own work and analysts’ work for accuracy, and document code and methods so they can be reused across projects.

Your next step

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About the role

We file this job under Analyst, by the work the posting describes.

Analysts answer business questions with data. They pull numbers with SQL, build reports and dashboards, and explain what changed and why to the people making decisions.

Most postings ask for SQL, spreadsheets, a dashboard tool such as Tableau or Power BI, and clear writing.

Unlike a data scientist, an analyst mostly explains what happened rather than building models that predict what will.

Job description

View original posting ↗

Senior Associate, Patient Analytics 

Role Overview 

We are hiring a Senior Associate who enjoys working hands-on with real-world data and turning it into answers pharma brand teams can act on. You will work on breast cancer engagements for US pharma clients, building the cohorts, algorithms and analyses for each client's requirements. Over time you will extend this work to other Oncology, Immunology and Rare disease areas. You will work closely with the engagement Manager and grow into leading workstreams yourself. 

Key Responsibilities: 

  • Build breast cancer patient cohorts from claims and EMR data, defining patients by subtype (HR+/HER2-, HER2+, TNBC), stage (early vs. metastatic) and biomarker status. 

  • Write and validate the logic behind core metrics: line-of-therapy assignment, regimen grouping, persistency, adherence, time on therapy and source of business. 

  • Track biomarker testing patterns (HER2, ER/PR, PD-L1) and identify patients who are tested but not treated, or treated without testing. 

  • Translate data outputs into clear charts and slides, and present findings in working sessions with client teams. 

  • Build and maintain data pipelines and Tableau dashboards for ongoing brand and launch tracking. 

  • Check your own work and analysts’ work for accuracy, and document code and methods so they can be reused across projects. 

  • Support predictive modeling work such as patient finding and predictive segmentation, where needed. 

Qualifications: 

  • Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Data Science, Engineering, Life Sciences). 

  • 3–5 years of experience in US pharma analytics, with most of it spent working directly with patient-level data. 

  • Must have: Hands-on experience on breast cancer patient analytics project, building cohorts, LOT or patient journey analyses yourself. 

  • Familiarity with oncology coding (ICD-10, NDC, J-codes) and experience with APLD/claims, EMR and lab datasets. 

  • Strong SQL and Python/PySpark skills; experience building dashboards in Tableau or similar tools. 

  • Good to have: Exposure to other Oncology, Immunology or Rare disease data, or to predictive / machine learning models. 

  • Clear communicator, detail-oriented and curious about the clinical story behind the data. 

Source details

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