Scientist II

About Us

ALS TDI is the world's leading nonprofit biotechnology organization dedicated solely to discovering and developing effective treatments for ALS. Operating without regard to profit or politics, our Watertown, Massachusetts-based lab is fueled by a global network of supporters unified to end ALS. Led by experts in drug development and individuals with ALS, we are driven by our mission to bring hope to those affected by this disease.

The Opportunity

We are seeking a highly skilled Scientist II to co-lead the management, analysis, and interpretation of complex natural history data associated with deep digital clinical phenotyping, as well as multiomics data including genomics, transcriptomics, metabolomics, and proteomics. As our research portfolio has grown, this role shares scientific leadership of the function with an existing domain expert and leads analytic planning and prioritization across a growing set of projects. This role will focus on the study of amyotrophic lateral sclerosis (ALS). The ideal candidate will possess a strong background in data science, statistics, and bioinformatics, coupled with a strong grounding in biomedical research methodologies and, ideally, direct experience in neurodegenerative disease.

What You'll Do

Analytic Planning and Grant Support:

• Co-lead analytic planning and prioritization across the research portfolio in partnership with the existing domain expert.
• Contribute to grant applications, progress reports, and other funder deliverables.

Data Management and Sharing:

• Develop and implement robust data management strategies for clinical natural history data and multiomics datasets.
• Oversee data acquisition, cleaning, curation, and integration from diverse sources to ensure data quality and consistency.
• Collaborate with internal and external stakeholders to facilitate data sharing initiatives and compliance with data governance policies.
• Maintain reproducible, version-controlled analytic code and documentation using Git and GitHub.

Data Harmonization and Integration:

• Lead efforts to harmonize heterogeneous datasets, including clinical, genomic, transcriptomic, and proteomic data, including single-cell, single-nucleus, and spatial modalities, to enable comprehensive analysis.
• Develop and apply advanced algorithms and methods for data integration to extract meaningful insights and identify correlations across different data modalities.

Data Analysis and Interpretation:

• Utilize statistical and machine learning techniques to analyze multiomics datasets, with a focus on identifying disease biomarkers, prognostic factors, and therapeutic targets relevant to ALS and other neurodegenerative diseases.
• Conduct exploratory data analysis and hypothesis testing to uncover patterns, trends, and associations within the data.
• Work closely with domain experts to validate findings and translate analytical results into actionable insights for research and clinical applications.

Communication and External Engagement:

• Communicate findings effectively through compelling data visualizations, reports, and presentations tailored to diverse audiences, including researchers, clinicians, and stakeholders.
• Collaborate with cross-functional teams to disseminate research findings through scientific publications, conference presentations, and other knowledge-sharing platforms.
• Serve as a scientific point of contact for funders and collaborators, and represent the work at conferences and collaborator meetings, which involves periodic off-site travel.

What You'll Bring

• Advanced proficiency in programming languages including R and/or Python along with Linux command line fluency.
• Comfort with technical documentation and with version control using Git and GitHub for collaborative, reproducible work.
• PhD or equivalent advanced degree in data science, bioinformatics, computational biology, or a related field.
• Proven track record of 5+ years of experience in data science, with a focus on biomedical data analysis and interpretation.
• Expertise in statistical modeling and machine learning applied to complex biomedical datasets, including longitudinal mixed-effects models, survival and time-to-event analysis, and the development and validation of prognostic models.
• Familiarity with cloud computing platforms (AWS, GCP, and/or Azure), including compute, storage, and access management for data sharing.
• Experience in neuroscience, neurology, or a related biomedical domain (ALS or other neurodegenerative disease experience strongly preferred), and familiarity with relevant clinical research methodologies and data resources.
• Experience working with natural history data and multiomics datasets.
• Familiarity with data from digital health technologies (e.g., wearable sensors, speech recordings, and app-based assessments) and with time-series methods for analyzing them.
• Familiarity with standardized clinical vocabularies and common data models, particularly the OMOP Common Data Model and OHDSI tooling.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with multidisciplinary teams and communicate technical concepts to non-technical stakeholders.
• Proven ability to manage multiple projects simultaneously, prioritize tasks, and deliver high-quality results within tight deadlines, and to coordinate contributions from others across a team.
• Familiarity with data sharing policies, ethical considerations, and regulatory requirements in biomedical research.

Nice to have: We do not expect any single candidate to have experience in all of the following areas:

Genetics and integrative genomics

• Whole-genome or whole-exome sequencing analysis, including variant calling and repeat-expansion detection (e.g., C9orf72).
• Integrative genomics linking cell-specific expression to genotype (e.g., eQTLs, allele-specific expression, GWAS loci, rare variants, colocalization).

Single-cell, spatial, and RNA biology

• Single-cell and single-nucleus RNA sequencing (scRNA-seq and snRNA-seq), ideally including snRNA-seq of human brain or spinal cord tissue.
• Single-cell experimental design and statistical analysis, including quality control, normalization, batch correction, donor-level effects, cell annotation, differential expression and abundance, and pseudobulk approaches.
• Single-cell multimodal analysis (e.g., scATAC-seq, 10x Multiome).
• Spatial transcriptomics or other spatial omics.
• Cell-state and trajectory analysis (e.g., pseudotime, RNA velocity, pathway and regulatory network analysis, cell-cell communication).
• Integration of bulk and single-cell data, including deconvolution of bulk RNA-seq.
• RNA splicing, transcript isoform, or RNA-protein interaction (e.g., CLIP-seq) analysis.

Functional genomics and cellular phenotyping

• Perturbational and functional genomics (e.g., CRISPR screens, RNAi or antisense oligonucleotide perturbations, transcriptional responses to compounds).
• High-content cellular phenotyping, including integration of microscopy-derived phenotypes with transcriptomic and other molecular data.

Proteomics, workflow engineering, and data standards

• Proteomics data analysis, particularly from affinity-based platforms (e.g., SomaScan, Olink), including normalization, quality control, and handling of platform-specific technical artifacts.
• Omics workflow engineering (e.g., Nextflow or Snakemake, containers, HPC or cloud pipelines), including reproducible processing from raw sequencing data onward.
• GA4GH standards and phenotype ontologies such as Phenopackets, Mondo, and the Human Phenotype Ontology.
• Interest in LinkML or similar tools for defining and validating data schemas.

What We Offer

Meaningful, Mission-Driven Work: Play a vital role in the fight against ALS. You'll engage passionate supporters and see the direct impact of your work on a mission that truly matters.

Flexibility & Collaboration: Enjoy a hybrid position supported by a highly connected, collaborative team.

Exceptional Benefits Package: We are proud to invest in our team's health, wealth, and well-being with a comprehensive benefits package:

• Outstanding Health Coverage: Medical insurance with a company-funded HRA that covers 100% of your deductible for you and your dependents, plus comprehensive dental and vision plans.
• Financial Security: A 403(b) retirement plan with a 4% company match and access to Flexible Spending Accounts (FSA).
• Complete Peace of Mind: We provide company-paid short-term disability, long-term disability, and life insurance at no cost to you.
• Generous Time Off: Recharge with our Unlimited PTO policy, in addition to 12 paid company holidays.

Engage Our Community: Represent ALS TDI and connect with our incredible supporters at major marathons and community events across the country.

A Culture of Respect & Integrity: Join a team where tenacity, resourcefulness, and compassion are at the heart of everything we do.

Join Us

Join our dynamic team at the forefront of neurodegenerative disease research, and contribute to advancing our understanding of ALS through innovative data-driven approaches.

ALS-TDI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.