Qureos Mentor

Generate:Biomedicines

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 The Role:
 
 
 
 We are looking for a pragmatic, curious data scientist who wants to learn how data can improve clinical trials and help turn careful analysis into better decisions.
 
 
 This person learns quickly, works well in environments where data security and governance are essential, and can help move from hypothesis to evidence with guidance from experienced clinical, statistical, and engineering partners.
 
 
 They will contribute to focused explorations across statistical modeling, trial operations, data quality, and decision support, helping test whether promising ideas are useful, trustworthy, and actionable.
 
 
 As the first Generator in this role, they will work closely with existing members of the Clinical AI Team, including a data engineer, a Bayesian-trained statistician, and a customer-focused product manager. They will be expected to bring initiative, care, and follow-through, while learning the habits of rigorous, transparent, decision-oriented clinical data science. They will also help establish good working practices for this new capability through careful, reproducible, well-communicated analysis.
 
 
 The data scientist will use their skills to help improve how clinical trials are planned, monitored, and understood. You will be part of a small team working to make clinical development more evidence driven.
 
 
 Your analyses, prototypes, and evidence packages will help the people running our trials make better decisions, with support from clinical, statistical, product, and engineering partners.
 
 
 This is not a reporting role, and the deliverable is not dashboards. The real deliverable is trustworthy evidence: careful analysis, clear communication, and follow-through that turn raw data into insights people can act on.
 
 
 This role is a good fit for someone who wants to work on meaningful clinical problems, develop ownership over time, and see careful analysis influence decisions in the real world.
 
 
 
 Here's how you will contribute:
 
 
 
 
 Trustworthy data.
 
 You will help the team work from data that is accurate, current, well-understood, and honest about its limitations. Because your work may inform important clinical and operational decisions, quality, provenance, and transparency matter.
 
 
 
 Turning data into evidence.
 
 You will contribute a quantitative, model-minded approach to well-scoped clinical and operational questions, working closely with senior statistical and clinical partners. You will learn to reason carefully under uncertainty, evaluate assumptions using evidence, and help the team distinguish between signals, hypotheses, and verified facts.
 
 
 
 Learning from decisions.
 
 You will not stop at producing an analysis. You will help track how analyses are used, learn what happened after decisions were made, and use that feedback to make future work stronger.
 
 
 
 Building with others.
 
 You will work closely with clinical, statistical, engineering, and product partners to understand the real-world context behind the data. Good answers will often come from combining technical rigor with curiosity, humility, and collaboration.
 
 
 
 The Ideal Candidate will have:
 
 
 
 We care about the mission first, but this is a technical, learning-oriented role for someone with solid analytical foundations and an interest in deepening their statistical and clinical trial expertise.
 
 
 The following will help set you up to succeed:
 
 
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 Applied statistics and data science: a foundation in applied statistics, with curiosity about Bayesian inference, hierarchical and small-data modeling, calibration, experimental design, A/B testing, and causal inference.
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 Practical data skills: experience with Python, pandas, and SQL, with the ability to work with multi-source datasets and contribute to reproducible, well-documented analysis workflows.
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 Messy data to useful evidence: experience working with messy, multi-source data and turning it into clear, well-supported analysis that others can trust.
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 Clear uncertainty communication: ability to communicate what is known, what is assumed, what is missing, and what confidence we should have.
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 Data honesty: care about the difference between a signal, a hypothesis, and a verified fact, and transparency about provenance and confidence.
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 Cross-functional collaboration: comfort working across functions, asking good questions, and translating technical analysis into practical implications.
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 Advanced degree in a quantitative / scientific field (e.g. MS or PhD)
 
 
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 These are what we are looking for, not a rigid checklist. Candidates who are still growing in some areas and bring relevant strengths in others are encouraged to apply.
 
 
 
 Who Will Love This Job:
 
 
 
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 Is motivated by the mission of helping patients benefit from better clinical development and wants their work to matter in that context.
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 Wants to understand the data, the problem, and the context behind both rather than staying at the surface.
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 Takes responsibility for assigned work, follows through carefully, and cares whether the work helps improve decisions or behavior.
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 Learns quickly and is comfortable with unclear or evolving problems, while knowing when to ask for guidance and how to make progress with imperfect information.
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 Communicates clearly, especially when the answer is uncertain, incomplete, or more nuanced than people expected.
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 Builds trust through rigor, transparency, and steady follow-through.
 
 
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 If you have that motivation and a real interest in working with data, the rest is learnable.
 
 
 
 About Generate Biomedicines
 
 
 
 We are a clinical-stage generative biology company pioneering the AI revolution in drug design and development. We are advancing a new approach to drug creation&mdash;one grounded in the ability to design proteins with defined biological intent. By integrating machine learning with large-scale experimentation, this approach aims to reduce the uncertainty, time, and cost associated with developing protein-based medicines.
 
 
 Founded in 2018, we are advancing a growing pipeline of clinical and preclinical programs across multiple disease areas and protein modalities. By unifying computational design and clinical development within a single operating model, we translate this approach into clinical-stage programs and are leading a shift from traditional drug discovery toward systematic drug generation.
 
 
 At Generate:Biomedicines, we collaborate across disciplines in new ways to invent and innovate. We bring diverse perspectives to a shared goal of delivering better medicines to patients in need, faster, guided by our values and leadership behaviors.
 
 
 Generate:Biomedicines is
 
 committed to equal employment opportunity
 
 regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 
 
 Recruitment &amp; Staffing Agencies
 
 
 
 : Generate:Biomedicines does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Generate:Biomedicines or its employees is strictly prohibited unless contacted directly by the Company&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Generate:Biomedicines and the Company will not owe any referral or other fees with respect thereto.
 
 
 
 
 Compensation:
 
 The base salary range provided reflects our current estimate of what we anticipate paying for this position. Your actual base salary will be based on several factors, including job-related skills, experience, internal equity, relevant education or training, and market dynamics. In addition, you will be eligible for an annual bonus, equity compensation, and a competitive benefits package.
 
 
 Per Year Salary Range
 
 
 $140,000&mdash;$170,000 USD
 
 
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Data Scientist I

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Data Scientist I