Job Description

Job Description

Job Description

Lynx Dx is a dynamic start-up biotechnology company specializing in molecular diagnostics. Our flagship product, MyProstateScore 2.0, is a non-invasive urine test that analyzes a comprehensive array of 18 gene transcripts, including T2:ERG, to predict the presence of clinically significant prostate cancer. We are a highly productive organization that thrives on innovation and results, seeking motivated and independent team members to help us advance diagnostic solutions in oncology.

As the Biostatistics / Bioinformatics Scientist at Lynx Dx, you will take a pivotal role in designing and implementing statistical models and computational frameworks to support the development of diagnostic and prognostic tests. This position emphasizes biostatistical expertise and involves leading efforts to analyze genomic and clinical data, developing predictive models, and validating risk scores for prostate cancer diagnostics. Additionally, you will receive comprehensive training in all aspects of product development within the oncology diagnostic space.

You will work closely with multidisciplinary teams, including Medical Affairs, Clinical, Regulatory and IT to translate molecular insights into actionable diagnostic tools. The ideal candidate is highly motivated, independent, and thrives in a fast-paced environment, ready to make significant contributions to a growing start-up with a mission to transform molecular diagnostics.

This is a unique opportunity for a motivated biostatistics professional to join a cutting-edge biotechnology start-up and make a lasting impact on the field of oncology diagnostics. If you are passionate about combining statistical expertise with genomics to drive innovation, we encourage you to apply.

This is a full-time role based in Ann Arbor, MI, with flexibility for on-site, hybrid or remote work, reporting directly to the Director of Research & Development.

Key Responsibilities:

• Develop and validate biostatistical models for risk prediction, diagnostic performance, and prognostic evaluation in oncology.
• Lead the statistical analysis of genomic and clinical datasets, including regression, Bayesian inference, and machine learning techniques.
• Collaborate on the design, execution, and interpretation of experiments to evaluate diagnostic biomarkers.
• Contribute to the development and refinement of bioinformatics analysis pipelines, integrating biostatistical rigor into all stages of pipeline design and implementation.
• Communicate findings through reports, presentations, and scientific publications, ensuring clear documentation of methodologies and results.
• Collaborate with cross-functional teams to align biostatistical and bioinformatics goals with clinical and product development objectives.

Qualifications:

• Ph.D. in Biostatistics, Bioinformatics, Computational Biology, Genetics, or a related field, with 1-5 years of relevant work experience.
• Deep expertise in statistical methods and algorithms for genomics data analysis, including but not limited to machine learning, regression analysis, and Bayesian inference. Experience with deep learning is a plus.
• Proficiency in R and Python for statistical analysis, data visualization, and modeling. Familiarity with tools like ggplot and dimensionality reduction techniques is preferred.
• Experience analyzing high-throughput sequencing data (e.g., RNA-seq, exome-seq, targeted sequencing).
• Familiarity with automated primer and probe design for multiplex assays is advantageous.
• Excellent communication skills with a proven ability to work effectively in cross-functional, collaborative environments.

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