LIMS Product Manager

Computing · South San Francisco, California
Department Computing
Employment Type Full-Time

The Opportunity

At insitro, we are combining human biology and machine learning to discover new therapeutics.

The heart of our strategy is to produce large data sets that will drive machine learning and yield key biological insights. This strategy requires a seamless, robust, and effective operation that simultaneously spans multiple projects, some partnered and some in-house. Our success relies 

on working across functions, including high-throughput biology automation, functional genomics, data science, machine learning, translational science, and drug discovery, to ensure that projects have what they need for successful execution. 


We are seeking a LIMS Product Manager to lead our lab automation and data generation efforts to produce high dimensional and high quality data for machine learning-based drug discovery. In this role, you will be a product owner for the vision of a software enabled lab. You will collaborate with Process Engineering, Software Engineering, Scientists, and Lab operations to achieve the standardize, scale and maintain high-quality lab data generation. Lab data is central to this role, and so you will also coordinate the planning, capture, and management of experiment and process data for all phases of drug discovery workflows. By working with functional and project teams, you will also define the types of data to capture to enable deeper insights to process and experimental results.

  

You will be joining an exciting biotech startup that has long-term stability due to significant funding, but is very much in early formation. A lot can change in this early and exciting phase, providing many opportunities for significant impact across several functions and disciplines. You will work closely with a very talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us in leading the way to better medicines through predictive models by integrating machine learning and biology at scale.


The Role

The LIMS Product Manager will lead the team through the full software development life cycle for building out a high quality and automated lab:

  • Learn and empathize with lab stakeholder needs.
  • Develop requirements and long-term vision for collecting and consolidating data from a wide range of stand alone and high-throughput drug discovery workflows.
  • Document needs as requirements and synthesize information to discover additional non-obvious needs.
  • Lead a cross-functional team spanning Process Engineering, Software Engineering, Scientists, and Machine Learning to design insitro’s LIMS strategy.
  • Develop mockups of views to validate needs and provide clear communication to Software Engineering.
  • Execute on the LIMS product vision by staging work into achievable milestones that deliver continuous incremental benefits.
  • Use your understanding of design tradeoffs to manage risk and maintain timelines.
  • Lead the Software Engineering team through an agile software development process including sprint planning, demos, UAT, and retrospectives. In addition, the LIMS PM will lead the lab operations through system validation, training, and support.
  • Champion lab data quality. Develop a fine-grain understanding of key indicators of data quality, design key metrics, and hold the team accountable for achieving LIMS data quality goals.


About You

  • Advanced degree - Masters or PhD in computational or natural sciences - or  equivalent experience / education. The successful candidate will have demonstrated a superb ability to quickly scale learning curves across scientific and technology disciplines.
  • 5-10 years of relevant work experience in technology or life sciences
  • Project management and software development lifecycle experience especially in a production lab environment.
  • 3+ years experience in managing complex projects that involve facilitating cross functional communication and collaboration
  • Ability to communicate effectively and collaborate with people of diverse backgrounds and expertise 
  • A bias to action, a detail-oriented mindset, and the ability to operate effectively under ambiguous, rapidly changing circumstances
  • Passion for making a difference in the world


Nice to Haves

  • Experience working at an early stage startup
  • Exposure to computational methods relevant to microscopy, DNA sequencing, genomic analysis, and chemistry
  • Experience in high-end engineering technologies in the biomedical space
  • Experience scoping projects and gathering technical requirements
  • Knowledge of lab equipment and drug discovery workflows
  • Familiar with the management of Electronic Lab Notebooks

About insitro

insitro is a data-driven drug discovery and development company using machine learning and high-throughput biology to transform the way that drugs are discovered and delivered to patients. The company is applying state-of-the-art technologies from bioengineering to create massive data sets that enable the power of modern machine learning methods to be brought to bear on key bottlenecks in pharmaceutical R&D. The resulting predictive models are used to accelerate target selection, to design and develop effective therapeutics, and to inform clinical strategy. insitro was launched in 2018 with a Series A of $100M funded by top investors including a16z, Arch Venture Partners, Foresite Capital, GV, and Third Rock Ventures.

The company has announced collaborations with Gilead Sciences in the area of NASH (2019) and Bristol Myers Squibb in the area of ALS (2020) and, in mid 2020, completed a Series B financing of $143M including current investors and new investors Canada Pension Plan Investment Board (CPP Investments), T. Rowe Price, BlackRock, Casdin Capital and other leading investors. The company is located in South San Francisco, CA. For more information about insitro, please visit the company’s website at www.insitro.com 

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  • Location
    South San Francisco, California
  • Department
    Computing
  • Employment Type
    Full-Time