How often do you get the opportunity to be on the ground floor of a big and important mission? As a Senior Data Scientist for Dropbox's AI-first journey, you will join a team of top-tier data scientists and become an integral part of the product organisation, helping to scale this new business.

You will partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities' long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritise ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, drive measurable business impact, and proactively engage with business stakeholders with minimal direction
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Compensation

US Zone 2: $173,700-$234,900 USD US Zone 3: $154,400-$208,800 USD

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Joining on the ground floor of this startup team, you'll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities' long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritise ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, drive measurable business impact, and proactively engage with business stakeholders with minimal direction
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Compensation

Canada Pay Range $162,400-$219,600 CAD

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The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

Key responsibilities include:

• Independently pursuing cutting-edge research in AI applied to biological problems
• Building new models or fine-tuning existing models to identify biological changes resulting from disease
• Building models that achieve high accuracy and that generalise robustly to new data
• Applying contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms
• Working closely with ML Engineering partners to ensure that Freenome's computational infrastructure supports optimal model training and iteration
• Taking a mindful, transparent, and humane approach to your work

Requirements include:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modelling techniques
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modelling
• Practical and theoretical understanding of fundamental ML models like generalised linear models, kernel machines, decision trees and forests, neural networks
• Practical and theoretical understanding of DL models like large language models or other foundation models
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations
• A passion for innovation and demonstrated initiative in tackling new areas of research

Nice to have qualifications include:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models
• Experience in NGS data analysis and bioinformatic pipelines
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems

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