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Python Dash Plotly Jobs (Flexible Options) in Massachusetts

Plotly Dash, Streamlit, Spotfire, Retool, or similar tools for internal apps and data ... A Python coding exercise is part of the process Logistics and policy * Hybrid with office in ...

Plotly Dash, Streamlit, Spotfire, Retool, or similar tools for internal apps and data ... A Python coding exercise is part of the process Logistics and policy * Hybrid with office in ...

Python Dash Plotly information

What is a Python Dash Plotly developer?

Python Dash Plotly developers are professionals who specialize in building interactive web applications and data visualizations using the Dash framework and Plotly library in Python. Dash is a powerful open-source framework designed for creating analytical web applications without requiring extensive knowledge of front-end technologies. These developers use Dash and Plotly to create dashboards, data analytics tools, and visual reports that allow users to interact with complex data in real time. Their work often involves integrating data sources, designing user interfaces, and deploying applications for business intelligence or scientific research.

What are the key skills and qualifications needed to thrive as a Python Dash Plotly developer?

To excel as a Python Dash Plotly Developer, you need strong proficiency in Python programming, data visualization principles, and experience with the Dash and Plotly libraries, often backed by a degree in computer science or a related field. Familiarity with tools such as Git for version control, REST APIs, and cloud platforms, as well as knowledge of front-end technologies like HTML and CSS, is typically required. Excellent problem-solving, attention to detail, and the ability to communicate complex data insights clearly are crucial soft skills. These skills enable the creation of interactive, scalable data applications that effectively support business decision-making.

What are some common challenges faced by professionals working with Python Dash and Plotly in a collaborative team environment?

Collaborating on Python Dash and Plotly projects often involves managing code versioning, ensuring consistent styling, and coordinating updates to interactive dashboards. Teams may face challenges integrating user feedback quickly while maintaining code quality and performance, particularly when dashboards grow in complexity. Effective communication about data sources and deployment processes, as well as clear documentation, are key to overcoming these hurdles. Regular code reviews and adopting best practices for modular code can help ensure smooth collaboration and scalable dashboard development.

What is the difference between Python Dash Plotly vs Data Analyst?

AspectPython Dash PlotlyData Analyst
Primary RoleDeveloping interactive data visualization dashboardsAnalyzing data to generate reports and insights
Skills RequiredPython, Dash, Plotly, JavaScript basicsExcel, SQL, statistical analysis, data visualization
Work EnvironmentData visualization development teams, tech companiesBusiness units, consulting firms, finance, marketing
CertificationsPython certifications, data visualization coursesData analysis, Excel, SQL certifications

Python Dash Plotly professionals focus on creating interactive dashboards using Python, while Data Analysts interpret data and generate reports. Both roles require data skills but differ in technical focus and end goals.

What job categories do people searching Python Dash Plotly jobs in Massachusetts look for?

The top searched job categories for Python Dash Plotly jobs in Massachusetts are:

Informatics Engineer

Prime Medicine

Cambridge, MA • On-site

Full-time

Re-posted 19 days ago


Job description

About the role

We're hiring an Informatics Engineer to build the scientific data and computing platform that powers Prime Medicine's gene editing programs.

You will work in close partnership with our computational biology team and our cloud infrastructure team. The role suits someone who's comfortable owning a platform end-to-end, building the engineering foundations that scientists across the organization rely on, including data pipelines and APIs through to AI-enabled internal tooling. Your engineering judgment about what to build and how to build it will shape how Prime Medicine works with scientific data day-to-day.

What you'll do

  • Design and build the data platform connecting NGS instruments, laboratory informatics systems (Benchling), and AWS cloud compute; covering automated ingestion, provenance tracking, scalable storage, and observability.
  • Build production-grade APIs, SDKs, and internal tools that bring genomic data and analytical capabilities to scientists across the organization.
  • Build the orchestration layer for the automated, event-triggered execution of our scientific pipelines. The pipelines themselves (amplicon-seq, off-target analysis, and others) are co-developed with our computational biology team; you'll own how they run, scale, and integrate.
  • Ship AI-powered and agentic capabilities such as RAG over internal scientific data, agentic workflows with human-in-the-loop review, and internal copilots that streamline routine workflows across the organization connecting both science and business needs.
  • Build integrations across the scientific tool chain so data moves reliably between ELNs, LIMS, instrument software, and cloud compute.
  • Translate scientific requirements into reliable, maintainable software, helping bring research prototypes into production-grade systems.
  • Partner with computational biologists, lab scientists, and our cloud-support team to continuously improve platform performance, cost, and reliability.

What we're looking for

This is an Infrastructure engineering focused role, well suited to candidates whose primary background is software engineering, data engineering, or scientific platform engineering, with a strong interest in applying those skills to scientific problems.

Requirements:

  • 5+ years of full-time engineering experience (3+ for those with an MS or PhD) in production environments.
  • Strong Python programming skills.
  • Production AWS experience with depth in event-driven, cloud-native architectures, including AWS Lambda, EventBridge (or comparable event-routing infrastructure), and Infrastructure as Code with Terraform or CDK.
  • Docker / containerization, Git-based workflows, CI/CD, code review, and testing code in DEV/TEST environments before deploying to production.
  • A track record of building integrations and automations. Experience in a life-science related industry involving scientific or regulated data, such as biotech, pharma, healthtech, clinical informatics, scientific instrumentation, or agricultural genomics.

Nice to have

  • NGS expertise. Knowledge of NGS technology, workflows and pipeline architecture is strongly preferred.
  • Hands-on workflow orchestration experience. Familiarity with Nextflow/NextFlow Tower/Seqera Platform preferred.
  • Laboratory informatics experience with Benchling or comparable ELN/LIMS, as an operator, builder, or administrator.
  • AI / LLM tooling and agentic systems (LangChain, LangGraph, MCPs, RAG architectures).
  • Gene editing familiarity: CRISPR, base editing, prime editing.
  • GxP / 21 CFR Part 11 / regulated-software experience.
  • Plotly Dash, Streamlit, Spotfire, Retool, or similar tools for internal apps and data visualizations.
  • Experience managing or querying relational databases (PostgreSQL, MSSQL).

Interview process

The process includes a recruiter conversation, a hiring manager interview, and a small panel that includes computational biology, engineering, and wet lab partners. A Python coding exercise is part of the process

Logistics and policy

  • Hybrid with office in Cambridge, MA. We are not currently able to sponsor visas. US work authorization at the time of application is required.
  • Competitive base salary, equity, and standard benefits.