About the Role:

Stylus Medicine is seeking an intellectually curious and creative Director, who will serve as a key scientific leader on our Platform team, owning the computational strategy that drives large serine recombinase (LSR) engineering and clinical translation. This role sits at the intersection of protein engineering, multi-omics analysis, and AI/ML-driven design and will lead a high-impact team spanning NGS and computational biology while driving the analytical infrastructure and predictive capabilities needed to advance our proprietary LSR platform from discovery through translation.

Key Responsibilities & Accountabilities:

• Lead and develop a team of NGS and computational biology scientists, setting technical direction, mentoring team members, and fostering a collaborative, high-performance culture
• Lead computational efforts to design and optimize LSRs and related genome engineering proteins for genetic medicine applications, integrating sequence-function, structure-function, and protein-DNA interaction datasets to guide engineering campaigns
• Lead analysis of NGS data from LSR experiments — including amplicon sequencing, WGS, hybrid capture, and long-read sequencing — to quantify on-target efficiency and genome-wide specificity
• Build, apply, and critically evaluate predictive and generative models for protein variant and library design — including rigorous benchmarking of AI/ML approaches such as protein language models, structure prediction tools, and generative design frameworks
• Integrate proprietary screening data with public evolutionary and structural datasets to prioritize variants and identify engineering levers for activity, specificity, and developability
• Oversee the design, implementation, and deployment of robust, scalable computational pipelines for multi-omics data analysis, ensuring accuracy, reproducibility, and maintainability
• Provide scientific input into platform strategy, translating computational insights into actionable directions for the broader team
• Partner closely with the Screening, Genome Engineering, and NGS teams to design experiments, interpret complex datasets, and refine engineering hypotheses
• Contribute to patent filings, regulatory submissions, and publications

Qualifications & Skills:

• PhD in Computational Biology, Bioinformatics, Protein Engineering, Machine Learning or a related quantitative discipline, with 10+ years or Master’s with 14+ years of industry experience
• Demonstrated research in protein modeling, protein design, or computational biology through publications, preprints, or equivalent industry contributions
• Hands-on experience applying AI/ML methods to protein variant and library design, including protein language models, structure prediction, and generative design approaches (e.g., AlphaFold2/3, RFdiffusion, ProteinMPNN, ESM)
• Expert-level proficiency in Python and/or R, with deep familiarity with data science libraries (e.g., Pandas, NumPy, Bioconductor, SciPy, PyTorch, or JAX)
• Experience with cloud computing platforms and workflow management systems
• Excellent communication and documentation skills, with a track record of effective collaboration in fast-paced, interdisciplinary environments

Pay Range; $245,000 - $265,000

Role Summary

Prime Medicine is seeking an AI & Informatics Engineer to join our AI Foundry and support our pipeline delivery.  This includes designing and building the data and computational infrastructure that powers our prime editing programs. This role spans laboratory informatics, NGS pipeline development, and AI-enabled tooling, giving the right candidate a direct line from the work they do to the therapies we develop. You will partner closely with research scientists, computational biologists and technical development professionals, turning raw data into reliable scientific insights, and building automation and AI capabilities that let teams work faster and smarter.

Our ideal candidate brings strong software engineering fundamentals, hands-on NGS pipeline experience, a practical understanding of modern AI frameworks, and the biological intuition to translate scientific needs into working systems. Equally welcome are candidates who entered this space from the life sciences side and have built serious software skills along the way.

This is an action packed and dynamic role where the successful candidate will be involved in multiple programs and activities, so excellent organizational abilities, communications and strong collaboration are critical. The ideal candidate thrives when working in a fast-paced environment, working with purpose, and making an impact for patients.

Key Responsibilities

NGS Pipelines and Data Infrastructure

• Design, develop, and maintain scalable bioinformatics pipelines for NGS data analysis, including amplicon sequencing for on-target editing quantification, using Nextflow and Docker to ensure reproducibility.
• Build and maintain data infrastructure connecting NGS instruments, electronic laboratory notebooks (e.g., Benchling), data repositories, and AWS cloud compute, including automated data ingestion, scalable storage, and provenance tracking.
• Build APIs, MCPs, dashboards, and other internal tools that expose genomic data and analytical capabilities to scientific and cross-functional teams.

Laboratory Informatics

• Support implementation and ongoing development of laboratory informatics systems, including data ingestion from key instruments and integration with laboratory data platforms such as Benchling.
• Support vendor relationships and delivery outcomes for external collaborators, driving requirements, managing implementations, and ensuring high-quality delivery.

AI-Powered Tools and Automation

• Build AI-powered and agentic capabilities that automate routine work, support scientific reasoning, and improve how data and knowledge flow across the organization.
• Develop reusable platform components for retrieval, orchestration, and model interaction, with human-in-the-loop workflows that make AI systems transparent and practical for scientific users.
• Identify and address automation opportunities and scalability bottlenecks across research and operational workflows.

Engineering Practices

• Write production-grade code using Git-based workflows, peer review, testing, CI/CD, and documentation best practices; convert research prototypes into robust, maintainable software.
• Build integrations between internal tooling and third-party platforms to support evolving scientific and operational needs.
• Participate in cross-functional projects spanning lab operations, software engineering, and bioinformatics; recommend best practices, system architectures, and design patterns.
• Perform code reviews and contribute to documentation of engineering and cross-functional practices.

Qualifications

Required

• BS with 5+ years or MS with 3+ years of industry experience in Engineering, Bioinformatics, Data Sciences, or a related field. Candidates with biotech or life sciences with substantial software experience are strongly preferred.
• Strong Python development; proficiency with Nextflow (or comparable workflow tools), Docker, AWS, Linux/Unix, and Git.
• Experience developing and deploying bioinformatic data infrastructure, particularly NGS analysis pipelines.
• Experience implementing or integrating laboratory informatics systems, preferably including Benchling.
• Experience developing and maintaining production-grade APIs and SDKs, and rolling out software tooling across an organization.
• Familiarity with LLM frameworks and practical judgment about where agentic approaches add genuine value.
• Track record of shipping software that scientific or technical users adopt and rely on.

Preferred

• Experience building and deploying AI-powered tools or agentic systems in production or research settings.
• Familiarity with gene editing applications (CRISPR, base editing, or prime editing), including amplicon-seq workflows and tools such as CRISPResso.
• Familiarity with relational databases and data visualization tools (e.g., Plotly Dash, Streamlit, Spotfire).
• Experience in a GxP or regulated software environment (21 CFR Part 11, GAMP 5).
• Experience owning vendor relationships and delivery outcomes for external collaborators in laboratory informatics contexts.

Why This Role

Prime editing is a precise technology, and that precision depends on strong informatics, software, and scientific infrastructure. If you believe that better systems, better automation, and better access to data can translate into safer and more effective therapies, this is the right environment. You will build tools that directly shape how Prime generates, analyzes, and acts on scientific data, while helping lay the foundation for programs to come.

Your Impact at LILA

We are seeking a strategic Product Marketing Manager (Life Science) to own go-to-market for Lila’s life science product portfolio. You’ll translate complex, closed-loop AI and lab capabilities—such as mRNA design, DNA construct optimization, and AI-driven medicinal chemistry—into clear, credible stories and compelling commercial offerings for:

• Biopharma and advanced therapy companies
• R&D and CMC leaders
• Data science / AI teams and scientific IT

In collaboration with the Life Science Product team, you will shape RNA and DNA design technology tiles, hit-to-lead and lead optimization offerings, and early commercial pilots. Your work will define positioning, launch plans, and evidence strategies that move prospects from curiosity to committed programs. You’ll articulate value, build differentiated narratives, and enable cross-functional execution across product, sales, and customer success to accelerate adoption and drive measurable business impact.

What You'll Be Building

Messaging & Positioning

• Define and continuously refine product narratives for Lila’s life science capabilities (RNA/mRNA design, DNA constructs, protein and small molecule optimization, AISF-powered workflows).
• Tailor messaging to specific personas (Heads of R&D, Therapeutic Area leaders, CMC, translational and bioinformatics leads, Scientific IT) and use cases (hit-to-lead, mRNA design, in vivo CAR-T data stories).
• Ensure all external materials reflect Lila’s master narrative on scientific superintelligence, safety, and multi-domain learning.

Go-To-Market Strategy & Launch

• Lead end-to-end GTM for new life science capabilities: from beta/pilot framing through general availability and expansion.
• Partner with Product, Commercial, and BizOps to define offer constructs (pilot scopes, pricing guardrails, AISF access models) and map the customer journey from first meeting to signed programs.
• Align roadmap milestones (new RNA/DNA or medicinal chemistry capabilities, app workflows) with external launch moments, events, PR, and sales cycles.

Content & Evidence Creation

• Produce technical and visionary content that makes capabilities tangible:
  • Use case briefs, technical one-pagers, solution guides
  • Decks for customer pitches, partner discussions, and scientific meetings
  • Blog posts, webinar scripts, demo narratives, and explainer videos in partnership with Brand/Creative
• Collaborate with Life Science (LS) Product, science, and commercial teams to turn pilots and tech tiles into case studies showing real impact

What You’ll Need to Succeed

Education

• Bachelor’s degree in Life Sciences, Bioengineering, Data Science, or a related field. MS/PhD a plus.

Experience

• 5+ years in Product Marketing or closely related roles at a B2B SaaS, life sciences technology, or AI/ML company, ideally supporting discovery, translational, or CMC/R&D teams.

Domain Expertise

• Working knowledge of the life science value chain (discovery → preclinical → early development; RNA/DNA/protein or small molecule workflows).
• Familiarity with lab automation, assay platforms, FAIR data principles, and AI/ML in drug discovery or therapeutics.

Technical Fluency

• Comfortable engaging with AI scientists, bench scientists, and engineering/IT stakeholders; able to translate closed-loop AI and AISF concepts into clear business value.

Communication & Storytelling

• Exceptional writing and presentation skills, with a track record of content targeting scientific and technical audiences.

Cross-Functional Collaboration

• Proven success partnering across Product, Sales/BD, and Marketing; able to influence without formal authority.

Startup Mindset

• Thrives in a fast-moving, highly cross-functional environment where both the product and category are evolving.

Bonus Points For

• PHD is a plus

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

Parabilis Inc. is seeking a highly talented and motivated Senior Data Scientist / Cheminformatician to support the platform discovery engine for Helicon^TM peptide drugs. Reporting to the Associate Director of Cheminformatics, the candidate will work collaboratively with biologists and chemists, leveraging skills in data science and cheminformatics to enable hypothesis generation and data insights for advancing Fog preclinical drug discovery.

You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team ranging from computational biology, bioinformatics, computational drug discovery, research informatics and data engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science from building the discovery pipeline to supporting and developing our discovery platform.

Responsibilities

• Provide scientific leadership and data science / (chem)informatics expertise towards, but not limited to, hit identification, targeted screening of Helical peptide library designs, hit prioritization, hit-to-lead progression using multi-objective optimization, new drug-target assessments, and advancing drug-pipeline projects towards the clinic
• Analyze peptide/chemical structure and property space to identify patterns / gaps that inform Helicon and monomer designs
• Adapt and implement data analytics and machine learning techniques towards predictive models of Helicon^TM properties
• Contribute to implementation and development of cheminformatics and research informatics systems and tools for Fog
• Work with IT and data engineering to enable enterprise-level cheminformatics solutions

Requirements

• MS or PhD in Data Science, Cheminformatics, Computational Chemistry or Computational Biology, Chemistry, Biophysics, Macromolecular sciences, Computer Science, or related scientific field with 5+ years of experience within the pharmaceutical or biotechnology field
• Proven track record of impact in a drug discovery program using informatics/computational techniques
• Demonstrated expertise with cheminformatics (e.g. RDKit, ICM, OEChem) and data science toolkits/libraries (e.g. Pandas, Scikit-Learn, and Numpy)
• Demonstrated understanding of critical assessment of molecule-property data and predictive model quality
• Demonstrated expertise in data analytics and solid grasp of statistical principles
• Experience with data visualization techniques and exploration tools (e.g Vortex, Spotfire, Datawarrior, DataGrok)
• Strong scientific programming skills (Python). Familiarity with modern pipeline tools is a plus.
• Excellent communication and collaboration skills that contribute to and inspire a vibrant community of drug hunters
• Experience with (chem)informatics analyses of peptides, machine learning, databases/enterprise informatics systems (e.g. Dotmatics), or cloud computing environments (e.g. Google, AWS, Azure) is a plus

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $145,000 -$ 175,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being. 

As an equal opportunity employer, Parabilis Medicines values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

Why Join Us?

As a member of the Parabilis Medicines team, you will be a part of an organization dedicated to creating extraordinary medicines for diseases with urgent unmet needs, harnessing our proprietary peptide platform to transform treatment possibilities for patients. Parabilis is a clinical-stage biopharmaceutical company dedicated to unlocking high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead asset, zolucatetide (FOG-001), is a first-in-class, clinically validated direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in millions of cancer cases annually, including in colorectal cancer, desmoid tumors, hepatocellular carcinoma and a range of other Wnt/β-catenin-driven tumors. In Phase 1 clinical trials, zolucatetide produced the first-ever clinical evidence that it can directly inhibit this interaction, once previously considered “undruggable” despite its role across multiple cancer types. Parabilis is also advancing investigational degraders of ERG and AR^ON into clinical development for the treatment of prostate cancer, as well as progressing other preclinical programs. Backed by a recent $305 million Series F financing, Parabilis is entering an exciting phase of growth and execution.

What’s the opportunity?

We are seeking a highly talented and self-motivated person to contribute to the development of the Computational Drug Discovery group, a strategic function in Data Science that is part of Parabilis’s platform discovery engine for HeliconTM stapled-peptide drugs.  The skill sets of the group includes state-of-the-art machine learning/generative AI, molecular modeling, cheminformatics and data science towards the discovery and development of HeliconTM stapled-peptide drugs.

You’ll be part of a data science team that is a central pillar of Parabilis’s innovative discovery platform and pipelines targeting “undruggable” genes of major therapeutic interest to patients. Our data science team is an integrated team, ranging from computational biology, bioinformatics, computational drug discovery, research informatics and engineering. We work at the interface of chemistry, biology, clinical and computational sciences, and are responsible for all aspects of data science, from building the discovery pipeline to supporting and developing our discovery .

Responsibilities

• Provide computational expertise towards, but not limited to, ternary complex designs for degraders and other proximity-based modalities, hit-to-lead progression using multi-objective optimization, initiating new projects, new drug-target assessments and advancing drug-pipeline projects towards the clinic.
• Identify, implement, and apply 3D modeling techniques for sampling HeliconTM peptide conformations in presence of a target, in ternary complex, and in different physiological environments.
• Analyze and derive 3D peptide-structure relationships.
• Exemplify scientific leadership by partnering across functions and working within a team of talented and passionate scientists to discover drugs.
• Interface with internal and external partners.

What you’ll need to be successful:

• PhD in Computational Chemistry, Protein Engineering, Chemistry, Physics, Macromolecular sciences or close-related field
• 5+ years of pharma/biotech industry experience in computational rational drug .
• Demonstrated experience with ternary complex design and understanding, peptide design or protein engineering and a good understanding of peptide structure-property relationships (e.g. helicity and amphiphilicity metrics, cell penetration).
• Demonstrated mastery of modern computational chemistry including, but not limited to, peptide folding and docking, use of co-folding foundation models, such as Boltz, structure-based design (receptor and ligand-based), scaffold hopping, docking and conformational analysis.
• An understanding of modern drug discovery including, but not limited to, medicinal chemistry, multi-parametric optimization, molecular recognition principles, and the ability to adapt and translate these principles to stapled peptides.
• Excellent communication and collaboration skills, with the ability to work well in a multidisciplinary environment
• Excellent organizational skills and attention to detail, with a strong passion for learning new concepts and technologies
• Expertise in one or more peptide modeling environments (e.g. ICM, Rosetta, Amber, GROMACS) and methods (enhanced sampling MD, Monte Carlo, MSM).
• Demonstrated understanding of critical assessment of molecule-property data and predictive model quality.
• Demonstrated understanding of experiments behind the data that can be translated to computational analysis.
• Experience with command line modeling applications.
• Familiarity with cloud computing environments.
• Strong scientific programming skills (Python) in a Linux environment.
• Experience with enterprise research informatics systems such as Dotmatics and chemical and biological data warehouses is a plus.
• Familiarity with concepts in machine learning.
• Familiarity with cheminformatics techniques is a plus.
• Familiarity with use of LLMs and IDEs, such as Cursor, to enhance workflows, productivity and innovation is a plus.
• Demonstrated use of AI tools in your current role and responsibilities is required. Advanced or innovated use of AI is a strong plus.

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $145,000 - $175,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

Why Join Us?

Parabilis Medicines is a clinical-stage biopharmaceutical company dedicated to creating extraordinary medicines that unlock high-impact protein targets long-considered undruggable. The company has developed a new class of stabilized, cell-penetrant alpha-helical peptides – Helicons™ – capable of modulating intracellular proteins that are inaccessible to traditional drug modalities. 

Headquartered in Cambridge, Mass., Parabilis is advancing a focused pipeline of multiple first-in-class therapies across both rare and common cancers. Its lead candidate, FOG-001, is the first direct inhibitor of the interaction between β-catenin and the T-cell factor (TCF) family of transcription factors, implicated in colorectal cancer, desmoid tumors, and a range of other Wnt/β-catenin-driven tumors. Parabilis is also advancing investigational degraders of ERG and ARON for the treatment of prostate cancer, as well as other preclinical programs. 

What’s the opportunity?

This role is the primary computational partner for one or more pipeline programs, working across both preclinical and clinical spaces to convert complex biomarker, mechanistic, and RWD/E datasets into clear, actionable insights for target, dose, indication, and combination strategy. Reporting to the Head of Computational Biology, a successful candidate will design and implement robust analysis workflows spanning in vitro and in vivo studies, early‑phase trials, and external data sources to refine patient selection and mechanism‑of‑action understanding. The ideal candidate will couple their prior experience in oncology with a deep understanding of bioinformatics methodologies, a strong computational skill set, and an ability to translate scientific challenges into technical solutions and analysis that informs team decisions.

Scope of the role:

• Strategic thinker, planner and implementer of computational biomarker and translational analyses for early‑phase oncology studies (e.g., FOG‑001 and ERG/AR degraders), from IND‑enabling work through Phase 1/2, ensuring continuity between preclinical and clinical datasets.
• Design and execute analysis plans for diverse biomarker modalities across preclinical models and clinical samples, including bulk and single‑cell RNA‑seq, DNA panels/WES, ctDNA, IHC/IF, multiplex protein assays, and other exploratory readouts.
• Synthesize, summarize and communicate findings in a clear, decision‑oriented manner to cross‑functional teams and governance, and contribute to internal decision making, conference abstracts, and manuscripts as appropriate.

Who you’ll be working with:

• Partner closely with discovery biology, translational scientists, clinicians, biostatistics, and RWD/E colleagues to define questions that leverage both preclinical and human data, and to design analyses that are statistically and biologically robust

Main tasks & duties for the position:

• Analyze preclinical in vitro and in vivo data (e.g., Helicon screens, xenograft/PDX models, pharmacology and PD studies) to characterize target engagement, pathway modulation, and resistance mechanisms, and translate these findings into clinical hypotheses.
• Analyze pre and on treatment patient biopsies and blood samples to quantify pathway modulation, signaling changes, and emergent resistance or sensitivity signatures, integrating with preclinical findings where possible.
• Develop, validate, and operationalize predictive and pharmacodynamic biomarker signatures for use in preclinical strategy, trial design, and RWD/E anchored analyses, including patient stratification and indication/expansion cohort selection
• Uses leading-edge knowledge of principles, concepts and practices and/or techniques to lead complex projects involving related departments; May have supervisory responsibilities

What you’ll need to be successful:

• PhD in Computational Biology, Bioinformatics, Statistics, Epidemiology, or related field, or MS with significant industry experience in translational, clinical biomarker, and/or RWD/E analysis in oncology.
• 7+ years of relevant post graduate experience (biotech/pharma or closely related), including direct work with both preclinical and clinical oncology datasets.
• Strong hands on experience analyzing biomarker data such as DNA sequencing, RNA seq (bulk and/or single cell), ctDNA, and tissue based assays (IHC/IF, multiplex platforms), with demonstrated impact on either discovery or development decisions, ideally both.
• Proficiency in Python and/or R, including data wrangling, statistical modeling, visualization, and best practices for reproducible research (version control, environments, documentation).
• Comfortable operating at the interface of discovery, translation, clinical development, and external data, with a track record of effective collaboration with non-computational colleagues.
• Excellent communication skills, with the ability to translate complex analyses into concise, decision ready narratives for diverse audiences.
• Demonstrated use of AI tools in your current role and responsibilities is required. Advanced or innovative use of AI is a strong plus.
• Able to work on-site and attend in-person meetings for the majority of time.

Core Values

Parabilis is a team of passionate pioneers who are trailblazing the future of precision medicine with the aim of making a meaningful difference in the lives of patients. The company is committed to promoting an inspiring and flourishing working environment for all employees across the business, in all departments, and driving innovation for patient benefit.

• Growth-Minded. We’re inventing a new class of medicines—one applicable to therapeutic targets that have been dreamt about, but always considered impossible to drug. Our work requires us to be curious, humble and adaptable.
• In(ter)dependent.We are fiercely independent as a leader in defying the limitations of current therapeutic modalities, and interdependent as a team as we work collaboratively to shift drug discovery paradigms and provide patients with better treatment options.
• Patient-focused.We are deeply focused on patient outcomes, and all energy in the company is focused on science as it translates to patient impact.
• All-In.We’re All-In on solving some of the hardest scientific challenges and delivering one of the most effective new classes of drugs in history.

The base salary target for this position is $175,000 - $220,000 per year, depending on experience, qualifications, and internal practices. Parabilis’s total compensation package also includes an annual target bonus, equity, and a comprehensive suite of competitive benefits designed to support our employees’ overall well-being.

As an equal opportunity employer, Parabilis values an inclusive workplace and welcomes applicants of all backgrounds and experiences. All qualified applicants will receive consideration for employment without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other factors prohibited by law.

About the Role:

Stylus Medicine is seeking an innovative, intellectually curious and team-oriented Principal Scientist to support our large serine recombinase (LSR) engineering platform. This individual will provide high-resolution efficacy and specificity analysis to advance our pipeline as well as support onboarding of new preclinical assays for regulatory submissions, ensure accuracy of our analysis pipelines and translate our wet lab experiments into computational insights that will enable engineering of our next generation LSRs.

Key Responsibilities & Accountabilities:

• Lead the analysis of NGS data from LSR experiments (like amplicon, hybrid capture, and long-read sequencing) to quantify target efficiency and specificity
• Build integrated workflows to annotate and characterize target sites by synthesizing proprietary datasets with large-scale public genomic databases
• Design, implement, and scale robust computational pipelines for multi-omics analysis
• Collaborate closely with the Screening, Genome Engineering, and Protein Engineering teams to design experiments and interpret results
• Develop and maintain internal databases and infrastructure to ensure experimental results are accessible, reproducible, and actionable
• Contribute to patent filings, regulatory submissions, and scientific publications

Qualifications & Skills:

• PhD with 5+ years or Master’s with 10+ years (or Bachelor’s with 12+ years) of industry experience in Computational Biology, Bioinformatics, or a related quantitative discipline.
• Strong expertise in experimental design, data processing, statistical analysis, and NGS data analysis
• Expert-level proficiency in Python and/or R, with extensive experience using data science libraries (e.g., Pandas, NumPy, Bioconductor)
• Experience with cloud computing platforms for large-scale data processing and with workflow management systems
• Excellent organizational, communication, and documentation skills, with demonstrated ability to work effectively in collaborative, interdisciplinary environments
• Strong scientific critical thinking skills, including the ability to evaluate approaches, synthesize complex data, and provide actionable recommendations
• Proven track record of working successfully across cross-functional teams with proactive communication and timely delivery

Pay Range: $180,000 - $195,000

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry.

Role

Linux Systems Engineers at Watershed engineer infrastructure to meet the high-performance computing needs of modern biology. Designing systems that keep pace with the explosive growth in the kinds and size of biological data, you will work in a highly-customized bare metal environment where our biocomputing platform and analyses run at scale. You will be tasked with engineering a new cloud experience while enabling our technology evolution in a disciplined way.

Responsibilities

• Build, manage, and deploy a large fleet of Linux servers
• Research new technologies and solutions, implement them or build better
• Be the connection between hardware and software
• Monitor system performance and manage capacity.
• Fix and analyze technical incidents, solve ad hoc technical problems.

Qualifications

• Experience composing infrastructure-as-code for a modern environment
• Demonstrate a software developer mindset, building tools when necessary
• Knowledge of virtualization, networking, and Linux Kernel internals
• Ability to clearly communicate your thoughts, ask the right questions, and defend your views
• Responsibility and ownership over your domain. 

About Watershed 

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry. 

About the Role 

Customer Success Engineers work at the intersection of software engineering, bioinformatics, and customer success to understand and fulfill customer support needs. 

Customers choose Watershed to analyze and share large biological data sources in flexible, powerful computing environments. Customers will engage you as a first escalation point — you will draw on a knowledge of Linux systems, software engineering, and bioinformatics to unpack and resolve requests.

You will track down support requests across the platform, partnering with our Product Manager and Head of Operations. Expect variety in the complexity and kinds of technology and bioinformatics challenges you face. As you troubleshoot recurring issues, you will document and elevate common requests and fixes to improve future support.

Responsibilities 

• Develop an intimate understanding of how customers use the Watershed platform.
• Analyze and share data on customer usage, activity, and trends. Suggest upsell opportunities and advise on account-specific insights.
• Triage, manage, and resolve incoming customer support requests. Requests will vary in complexity from Level 1 support to interrelated Linux, software, and bioinformatics issues.
• Establish and uphold company support standards. Create resolution metrics and expand support programs as needed. 
• Create & manage a system for documenting solutions and workarounds for recurring requests so team members can resolve similar issues quickly.
• Write platform guides and FAQs to support new feature rollouts. Develop case studies detailing tailored customer solutions.
• Directly report to the Head of Operations & CEO. Escalate key support insights (i.e., ‘buggy functions’ or common user misunderstandings). 
• Ensure an excellent user experience on the Watershed platform

Qualifications 

• 1-3 years of professional experience supporting technical and non-technical customers as a bioinformatician. Experience working in a bioinformatics consultancy is strongly preferred
• A working understanding of Linux commands, system troubleshooting, and Docker.
• Proficiency with any one of Bash, Python, or R. Familiarity with all three is preferred.
• Familiarity with bioinformatics, computational biology, or a Masters in Bioinformatics is preferred

About Watershed

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action, headquartered in Cambridge, Massachusetts, composed of people who have come together to enable outcomes while empowering the research of all those committed to changing lives — all while bringing transformational change to a $40 billion industry.

Role

Infrastructure Engineers at Watershed engineer infrastructure to meet the high-performance computing needs of modern biology. Designing systems that keep pace with the explosive growth in the kinds and size of biological data, you will work in a containerized environment where our biocomputing platform and analyses run at scale. You will be tasked with engineering a new cloud experience while enabling our technology evolution in a disciplined way.

Responsibilities

• Build, manage, and deploy an enterprise infrastructure. 
• Research new technologies and solutions, implement them or build better
• Be the connection between systems and software
• Monitor system performance and manage capacity.
• Fix and analyze technical incidents, solve ad hoc technical problems.

Qualifications

• Experience composing infrastructure-as-code for a modern environment
• Demonstrate a software developer mindset, building tools when necessary
• Knowledge of virtualization, networking, and Linux internals
• Ability to clearly communicate your thoughts, ask the right questions, and defend your views
• Responsibility and ownership over your domain

About Watershed 

Our vision is to become the leading biocomputing platform. The future of biology is in big data analysis, and we are on a mission to accelerate digital drug discovery with the Watershed Bio platform. Watershed enables scientists to conduct all essential analysis — from lab data to plot — with a single software platform. 

We have attracted some of the best bioinformatics, engineering, and commercial talent, and we are growing! Join a team that’s intellectually curious with a bias for action. Headquartered in Cambridge, Massachusetts, we are a team of people committed to empowering scientists to change lives — aiming to bring transformational change to a $40 billion industry.

About the Role

Watershed Bio is hiring a Performance Marketing Analyst to integrate and own reporting for all digital marketing activity for our growth stage biocomputing platform. You will assess & combine data from Watershed’s digital channels (including: website visitor behavior, gated content downloads, and PPC advertising metrics). You will understand how this data translates to our sales pipeline, analyze how we can optimize marketing spend to drive business growth, and advise & empower leadership to make data-driven decisions.

The right person will have a strong background in building reports and analyzing digital marketing activity across many fields. You should be a stickler for accountability and accuracy — and pride yourself on delivering actionable insights.

Responsibilities 

• Own marketing and sales reporting for leadership and our commercial team. Draw on data from Salesforce, Webflow, Google Ads, Google Analytics, and other sources. 
• Serve as subject matter expert for all online marketing data sources. Be the backstop for accuracy and guarantee the validity of reports and metrics presented to leadership.
• Analyze cost-per-click, cost-per-lead, and click-through-rates and advise on how to optimize marketing performance.
• Collaborate cross-functionally to identify and deliver the best paid media opportunities to drive business growth.

Required Qualifications 

• Bachelor’s Degree, preferably in Marketing, Business, Economics, or Data Science
• 3+ years of experience creating, delivering, and interpreting commercial reports drawing from Salesforce, Google AdWords, Google Analytics, Webflow, and other digital marketing data sources.
• Strong analytical and problem-solving skills with a demonstrated track record identifying and resolving inconsistencies in commercial data to drive B2B growth.
• A perfectionist approach and ownership mentality toward analysis and reporting metrics. You take the ramifications of data-guided decision-making seriously.
• Experience presenting reports to leadership in a team setting from a marketing, finance, or consulting perspective.
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