About Ontada
Be part of the team that’s poised to transform the fight against cancer. Backed by the strength of a Fortune 8 company (McKesson Corporation), Ontada® develops technologies used by the oncology community to deliver evidence-based, personalized care, as well as insights used by biopharma companies to accelerate drug development and support the entire treatment journey. Our work powers informed decision-making at every pivotal moment in oncology – from the treatment options presented to patients, to the operational considerations for oncology practices, to the design of clinical trials, to the commercial launch plans for new therapies. Together with our partners, we improve the lives of cancer patients.
What You’ll Do
The Director of Data Science and Machine Learning (ML) directs and executes Ontada’s technology roadmaps in ML and Natural Language Processing (NLP) Data Platform roadmap through close collaboration with Ontada commercial, chart abstraction and engineering teams. He/she follows the agile development methodology to rapidly iterate prototypes and scales them to platform re-usable capabilities in order to accelerate data product and insight delivery to health care and life science customers, while maintaining sustainable growth. Thought leadership in ML/NLP and excellent communication skills with the ability to resolve competing priorities are required for this position.
Responsibilities
Data Science and ML Leadership:
- Develop a comprehensive strategy of Data Science taking into account Ontada’s overall vision, the evolving health IT and data ecosystem, and productive application in AI
- Present and communicate the ML/NLP strategy and project to all stakeholders in Ontada and McKesson leaderships, as well as customers and prospects
- Direct full life cycle ML/NLP solutions, from planning, designing, technical implementation, troubleshooting, deployment, validation, and maintenance
- Be accountable to the data science backlog and constantly evolve it based on the latest changes in the business
- Manage conflicting priorities across different stakeholders
- Perform code reviews to guarantee high quality products
- Oversee technology implementation to automate data processes and inferences
- Direct annotation workflow and abstractor training process development
- Orchestrate across a multi-disciplinary team to create a unified strategy that drives business value
- Develop trust partnership with stakeholders through transparency and incremental delivery of value
- Manage third-party vendors
- Evaluate innovative technologies and tools prior to wider business adoption
People Leadership:
- Accountable for value prioritization for your team
- Constantly measure the success of your team’s projects and the products to ensure the team is on the right track to deliver value to Ontada business
- Able to draw out the best ideas from teams and individuals
- Build incredible teams and an operation that deliver data science product solutions in a timely and efficient manner
- A visible and active leader within the data science area that provides mentorship, feedback, coaching, and advice, also builds community around capability development initiatives
What You’ll Need
- 12+ years of experience in advanced analytics, machine learning, and natural language processing
- 4+ years of people management experience
- MSc, PhD and work experience in Data Science
- Must be authorized to work in the US (sponsorship is not available)
Critical Skills And Experience
- Experience in mining Claims and EHR (Electronic Health Records) data, preferably oncology related data
- Experience managing full lifecycle, from research to production, of machine learning data products
- Experience in Optical Character Recognition (OCR) and NLP for unstructured data analysis
- Knowledge of data curation and analysis packages (e.g., NumPy, Keras, PyTorch, Pandas, scikit-learn)
- Knowledge of NLP libraries, ontology-based and deep learning-based libraries, (i.e., Huggingface, SpaCy, NLTK, cTAKES, MetaMap, or John Snow Labs)
- Experience with modern cloud technologies in AWS and Azure
- Experience with ML workflow orchestration tools (e.g., Airflow, MLflow)
- Experience with Github, JIRA and Confluence
- Solves problems in unique ways by drawing from background and experience working in an array of contexts
- Experience in working in root cause identification and analysis
- Experience with healthcare data, real-world data, or clinical data
- Experience in team culture building with growth mindset
Additional Skills
- Excellent written and verbal communication skills
- Experience working in the life sciences or the bio/chemical research field
- Experience in oncology data and clinical workflow
- Demonstrated entrepreneurial mindset and self-direction, ability to teach others and willingness to learn new techniques
- Willingness to jump into projects and complex environments to make sense of ambiguous details in multiple domains
Technologies We Utilize
- NLP libraries, ontology-based and deep learning-based libraries, (i.e., Huggingface, SpaCy, NLTK, cTAKES, MetaMap, or John Snow Labs)
- Cloud Technologies: AWS and Azure
- ML workflow orchestration tools (e.g., Airflow, MLflow)
- Github, JIRA and Confluence
Work Environment
This is a REMOTE work location ideally based in Boston but will consider remote locations in the Eastern or Central United States. You can expect some occasional travel (up to 10%).