Duties: Contribute to the design and analysis of engineered mammalian cell lines; Work closely with bench scientists by guiding experimental workflows and quantitative measurements to ensure statistical rigor; Regularly dive deep into the multiomics stack, innovate on analysis techniques, and present findings to our organization, leadership, and partners; Explore novel genomics and machine learning algorithms
Requirements: You are a highly skilled technical leader in computational biology interested in engineering biology, and with years of experience in an industry or research position; You embrace ambiguity and always drive for impact. In addition, you have extensive experience with software scripting (e.g., Python and R), bioinformatic toolsets, high-performance and cloud computing, a strong foundation in statistics and statistical design of experiments, a collaborative mindset, and a passion for continuous learning

Duties: Directs one or more projects including multiple clinical trials, observational studies, or real world data (RWD) investigations. Also includes presentation to the Peer Protocol Review Committee (PPRC) or other internal senior review boards; Manage a team of direct reports including their performance and development. Mentors project team members and promotes effective team operation and cross-functional collaboration; Possesses an expert understanding of modern drug discovery and development processes; Represents Biostatistics as a member of cross functional teams, providing strategic input and expert technical guidance to elicit meaningful and/or productive outcomes. Sets the technical and scientific directions of the project(s)
Requirements: Ph. D. or master's degree in Statistics or Biostatistics; Typically requires 10 years of experience with a Ph.D. or 13 years of experience with a master's degree, or the equivalent combination of education and experience

Duties: Data Processing: Uses existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization. Adapts tools when necessary; Data Analysis: Performs routine analysis for which established tools exist and are considered reliable; Keeps up with the computational biology literature to assure pipelines components are up to date. Adapts tools when necessary; Data and Software Management: Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates. Evaluates published tools and updates pipeline as necessary. Writes scripts that perform this automatically
Requirements: Bachelor's degree required in a STEM field. Master’s degree preferred in bioinformatics, computational biology, statistics, biostatistics, computer science and/or the life sciences; 2 years with Bachelor’s degree or 1 year with Master’s degree; academic research experience or authorship in scientific publications experience may substitute for work experience

Duties: Develop computational methodology and perform critical analyses to support development of new products and improvements to existing products, both as an individual contributor and/or as a team leader; Collaborate with cross-functional teams including members from assay development, software engineering, marketing, quality, regulatory, and others to execute complex product development projects; Work closely with bench scientists to develop and optimize new wet-lab protocols in concert with computational biology development efforts; Analyze large genomic and epigenomic datasets using cutting-edge computational biology methods to identify genomic alterations and biomarkers associated with cancer onset and progression and to craft novel tools to detect those patterns
Requirements: PhD in a life science or computational discipline; 5+ years of postdoctoral research or professional experience related to NGS or cancer diagnostics

Duties: patient risk stratification in order to determine which patients are in most urgent need of care; application of causal analysis to determine the treatment effect of Pearl’s platform; analyses in the vein of health economics to find “hot spots” of inefficient care management across our geographically dispersed and heterogeneous network of PCPs; financial modeling of the economic outcomes of PCPs in a variety of VBC programs, and; the development of analytical pipelines and reporting to empower business stakeholders to make informed evidence-based decisions
Requirements: Graduate degree in statistics, applied math, computer science, engineering or a related field and/or 10+ years of experience in performing results-driven quantitative analysis in a collaborative environment; Demonstrated delivery of impactful quantitatively-based initiatives or products, focusing on technical leadership, project management, and collaboration with cross-functional stakeholders; Experience working with many different types of data sets, including multimodal data. Ideal candidates will have deep experience in healthcare analytics, particularly in the Medicare value-based care space

Duties: Owning and leading various projects, serving as a subject matter expert; Developing and implementing bioinformatics tools and pipelines in cloud environment; Collaborating with DFCI software engineering and data science teams as well as interacting with external cloud and other technology vendors; Meeting, consulting, and providing computational and informatics support to various DFCI scientists and independent faculty members in designing and executing key biomedical projects; Collecting, analyzing, interpreting, and integrating complex biomedical data; Delivering results for projects and generating relevant reports
Requirements: Bachelor’s degree required in a STEM field. Master’s degree or PhD strongly preferred in bioinformatics, medical informatics, computational biology, statistics, computer science/engineering, or a related quantitative field; Deep bioinformatics skills at the interface between bioinformatics programming and understanding of biological and clinical problems; Experience in analysis of the next generation sequencing data, e.g. WXS/WGS, RNA-Seq, etc; experience in single-cell and/or ctDNA data analysis is a plus

Duties: Data Processing: Uses existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization. Adapts tools when necessary; Data Analysis: Performs routine analysis for which established tools exist and are considered reliable; Keeps up with the computational biology literature to assure pipelines components are up to date. Adapts tools when necessary; Data and Software Management: Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates. Evaluates published tools and updates pipeline as necessary. Writes scripts that perform this automatically; Manuscript Preparation: Independently edits and drafts the computational biology sections of a manuscript; assists in writing the results section; checks manuscripts for numerical accuracy; prepares tables and figures; Grant Preparation: Helps to formulate specific aims, explains options for experimental design,...
Requirements: Bachelor's degree required in a STEM field. Master’s degree preferred in bioinformatics, computational biology, statistics, biostatistics, computer science and/or the life sciences; Experience with principles of experimental design and the modern data analysis paradigms is required

Duties: In this role you will support the design and development of new tools and platform components to improve existing platform capabilities and extend the platform to new research areas. You will work closely with other members of our team as well as our customers and partners to identify most pressing challenges and address them using cutting-edge computational biology and machine learning applications
Requirements: PhD in bioinformatics, computer science or a related discipline; 5+ years’ experience (in industry or academic environments, work towards PhD counts) in bioinformatics, data science, scientific software development or related role; Deep knowledge and experience analyzing large omics and molecular data either from industry or academia; Experience with NGS platforms, systems biology and machine learning; Advanced skills in Python and/or R

Duties: Conducts all scientific and operational statistical work for multiple clinical trials, observational studies, or real world data (RWD) investigations; Leads biostatistics projects or major components of a project including work allocation and review; May include presentation to the Peer Protocol Review Committee (PPRC) or other internal senior review boards; Possesses an advanced and in-depth understanding of modern drug discovery and development processes; Represents Biostatistics as a member of cross functional teams, providing input and specialized technical guidance to elicit meaningful and/or productive outcomes; Authors study Statistical Analysis Plans (SAPs), including table, figure, and listing (TFL) shells. Develops Cross-functional Data Review (xFDR) plan, Key Reports Memo (KRM), and Data Dissemination Plan (DDP) in order to facilitate the review, summary, and dissemination of key study data/results
Requirements: Ph.D. in Statistics or Biostatistics; Typically requires 7 years of experience with a Ph.D

Duties: Collaborates with Clinical Development, Clinical Pharmacology, Regulatory and Clinical Operations expertise areas to design clinical trials; Writes the statistical sections of clinical trial protocols, while consulting with internal and external experts; Contributes to or prepares statistical analysis plans and Data Presentation Plans; Collaborates with Data Management, Clinical Development, Clinical Pharmacology and Clinical Operations on design of eCRFs; Provides statistical guidance on conduct of ongoing trials; Collaborates with Statistical Programmers on summary and analysis of trial data. Writes and/or reviews ADS and ad hoc analysis specifications
Requirements: PhD in Biostatistics, Statistics, or equivalent with at least 4 years pharmaceutical biostatistics experience or MS with at least 6 years of relevant experience; Excellent written and oral communication skills; Excellent presentation and interpersonal skills; Experience programming in SAS; Experience with simulations (design, implementation and interpretation); Understanding of ICH GCP as well as general knowledge of industry practices and standards; Familiarity with R programming language and other statistical software, including EAST

Duties: Conducts advanced scientific and operational statistical work for multiple clinical trials, observational studies, or real world data (RWD) investigations, including the design, development and execution of the technical/statistical infrastructure; Possesses an advanced understanding of modern drug discovery and development processes; Represents Biostatistics as a member of clinical trial teams, providing input and technical guidance to elicit meaningful and/or productive outcomes; With minimal guidance, authors study Statistical Analysis Plans (SAPs), including table, figure, and listing (TFL) shells. Develops Cross-functional Data Review (xFDR) plan, Key Reports Memo (KRM), and Data Dissemination Plan (DDP) to facilitate the review, summary, and dissemination of key study data/results; Collaborates with statistical programming and other functions to ensure timely delivery of TFLs with good quality
Requirements: Ph. D. or master's degree in Statistics or Biostatistics; Typically requires 3 years of experience with a Ph.D. or 6 years of experience with a master's degree, or the equivalent combination of education and experience

Duties: Perform methodological and/or collaborative research under the direction of the lab’s PI; Design and carry out analyses of datasets; Work directly with “bench” scientists in analyzing data generated from individual projects; Prepare and deliver presentations as needed; Interact with other members of the lab as well as the lab’s scientific collaborators; Assist in grant and manuscript preparation
Requirements: PhD, MD, PhD-MD or doctoral equivalent degree; Background in applied or pure mathematics, statistics, bioinformatics, machine learning or computational biology; interest in cancer biology and work experience in computational biology and/or biostatistics are preferred; Knowledge of mathematical modeling and evolutionary theory as related to cancer, and/or knowledge of biostatistical methods and bioinformatics software and the ability to create novel analysis platforms desired; Experience in statistical computing, preferably in a biological research setting

Duties: The biostatistician will work with multidisciplinary teams on the design and analysis of research studies, results summary and interpretation, and manuscript/report preparation. There will be opportunities to work with the faculty biostatisticians on statistical methods development projects
Requirements: Masters degree in Biostatistics, Statistics, or a related field with strong quantitative training; Minimum of two years of related experience

Duties: You will deploy machine learning and data-science to simplify shopping experience for pet-parents, to maximize reach and discovery of new products of Chewy vendors and helping create a win-win ecosystem; Directly influence and collaborate with Product and Engineering leaders to evolve solutions using applied science to improve selection, ranking, relevance, deal-offerings, click through prediction models, dynamic bidding, and auction algorithms for Chewy advertising solutions; You will lead new models from ideation to experimentation, and eventually to production delivery to improve Chewy products offerings and advance applied science applications; Publish research papers in leading ML/AI/Advertising conferences solving problems for scale using innovative modelling
Requirements: An advanced degree (M.S., PhD, or equivalent experience) in Operations Research, Statistics, Applied Mathematics, Data Science or related field or 10+ years’ experience designing optimization and machine learning solutions for large scale applications; Ability to understand and apply advanced mathematics and DS methodologies; Experience in building distributed pipeline, tuning, optimizing and evaluation; Experience with multiple techniques that include Predictive Models (Time Series and Regression), Linear Programming, and Classification, Search, Ranking or large-scale embeddings

Duties: The biostatistician will work with multidisciplinary teams on the design and analysis of research studies, results summary and interpretation, and manuscript/report preparation. There will be opportunities to work with the faculty members on methods development projects and first-authored manuscripts
Requirements: Masters degree in Biostatistics, Statistics, or a related field with strong quantitative training; Minimum of two years of related experience

Duties: Work with bench scientists to develop experimental hypotheses and help design computational pipelines; Analyze high throughput molecular readouts including proteomics, RNAseq, single cell and spatial platforms and contribute to data interpretation and biological conclusions; Help building databases and visualizations using internal and external datasets; Manage and automate storing and integrating multi-omics data into databases hosted in the cloud; Contribute to scientific and strategy discussions to advance and improve Lilly Bioinformatics
Requirements: Masters degree in biological data analysis and management, bioinformatics, computational biology or similar and at least 1+ years of relevant experience; Familiarity with Linux shell scripting and other commonly used programming languages; Experience working with high performance computing in a distributed/cloud environments; Demonstrable analysis experience with omics or relevant datasets

Duties: Develop, design, clean, manage, and analyze data from all internal data sources using Unix and PC software including clinical information systems, automated medical records, hospital claims, outpatient claims, pharmacy, enrollment and benefits data. In addition to utilizing internal databases, will also utilize data developed from surveys, medical chart reviews, and external sources such as state-based registries; Develop automated scripts for frequent updating of analytic datasets to add information in near-real time including developing reconciliation procedures; Develop scripts to construct and receive routine HL7 messages to be used for information exchange in building data assets
Requirements: BA/BS in public health, quantitative social sciences, economics, statistics, mathematics or related field required. MA/MS in related field (e.g., statistics, quantitative social sciences, public health, epidemiology, economics or mathematics) preferred; Minimum 5 years of SAS programming experience, including experience as a senior level SAS developer in a healthcare-related setting. Extensive SAS macro development experience, including but not limited to the development of applications/systems that are exclusively macro- and table/data-driven. SAS hash object programming experience, including but not limited to its use in table merging/joining and look-up techniques. Experience writing and reviewing functional and technical programming specifications