TL
Total Life, Inc.
Data Scientist

Biostatistician / Data Scientist (Contract, Part-Time - Research Collaboration)

HybridMidData Scientistposted 1mo ago
Role summaryAI-generated

Develop and apply statistical and machine‑learning models to longitudinal behavioral‑health data to predict near‑term suicide risk. Collaborate with clinicians to design analyses, build pipelines, and translate findings into actionable insights for telehealth interventions.

Skills required

About this role

About Total Life
Total Life is a behavioral health telehealth practice serving older adults, with 200+ licensed clinicians across 49 states. Most of our patients reach us through Medicare and commercial insurance, and a large share are aging adults who fall outside traditional VA and specialty mental-health infrastructure. Because we deliver care remotely and repeatedly over time, we hold something unusual: dense, longitudinal behavioral-health measurement on an older-adult population that is rarely captured at this scale or cadence.

The research
We are building a research program around a simple but underexplored idea: most suicide-risk detection treats risk as a fixed state, measured once. We want to test whether the dynamics already present in routine care — how symptom scores move over time, and how patients engage with care as those symptoms change — carry information about near-term risk that standard one-time screening misses. The initial project is a retrospective study on fully de-identified data (no new data collection, no patient contact), developing and validating a multimodal risk-detection model and quantifying its incremental value over standard screening. This work is being submitted for federal research funding, and the person in this role would be a named co-investigator on that application.

The role
You would lead the statistical thinking behind this work — design and analysis, not just execution. Specifically:

  • Serve as co-investigator on a federally funded research application (biosketch and defined effort commitment required)
  • Design the statistical and validation plan: power / sample-size analysis for a rare-event outcome, model evaluation, discrimination and calibration, temporal validation
  • Advise on analytic methods for de-identified behavioral-health and claims data, including de-identification standards
  • Partner with our clinical and engineering teams to guide model development and interpret results responsibly

What we're looking for

  • PhD (or equivalent) in biostatistics, statistics, or a closely related field
  • Demonstrated experience building risk-prediction models, ideally with EHR, claims, or longitudinal healthcare data
  • Working knowledge of rare-event / class-imbalance methods and prediction-model reporting standards (e.g., TRIPOD)
  • Comfort with de-identified clinical data and methods such as HIPAA Expert Determination
  • US-based and able to be named on a US federal (DoD/NIH) research application
  • Prior experience on federally funded research (NIH/DoD) is a strong plus

Engagement
Part-time / contract, remote. Compensation commensurate with experience and scope. Immediate start preferred given active research timelines, with potential to grow alongside our research program.

✕ position closed

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