Data Scientist (senior to staff level) at Future Evidence Foundation

Our mission at the Future Evidence Foundation is to dramatically improve lives by changing the way the world creates and uses knowledge. Covidence is our SAAS platform that enables health & science research teams to rapidly synthesise and uncover actionable insights from existing research in the world. We’re a well-funded not-for-profit and a world leader in our field.

The Opportunity

Covidence is seeking a senior or staff level Data Scientist to join our team. You will be reporting to the CTO and will be responsible for discovering, developing and deploying solutions to accelerate the systematic review workflow.

While we continue recruiting and building our Data Science capabilities at Covidence, you will be the sole Data Scientist and will work within a cross functional team Product & Engineering team of 15 people. The team has already launched features that use external machine learning models e.g. to drive sort orders, to classify studies. We now want you to help us build and operationalise our own models. We’re early on this journey and have an initial implementation of extracting structured information from study documents, but we’re keen for you to help define the future roadmap and develop the next generation of AI and automation features for our users.

The potential for Large Language Models (LLMs) and Natural Language Processing (NLP) to unlock scientific knowledge and make a difference in the world is huge. This role is a chance to use your skills to be part of that change.

The ideal candidate will be a great communicator that has had recent hands-on experience building and deploying ML models that have solved user problems.

You’ll get to:

• Collaborate with the product and engineering team to identify areas for automation and improvement
• Design and develop ML algorithms for NLP tasks
• Analyse data and conduct experiments to improve the accuracy and efficiency of models
• Develop processes and frameworks to measure and evaluate the fit for purpose of models for our users
• Work alongside engineers to deploy models that can be integrated into Covidence’s systematic review process
• Stay up to date with the latest advancements in ML and NLP and apply them to our product
• Collaborate with leading ML practitioners in the research synthesis space to fundamentally change the way the world derives accurate insights from global research output

What you bring:

• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills
• Deep hands-on experience in ML
• Experience deploying ML models to production
• Experience in large language models
• Experience with NLP techniques and tools, such as spaCy, NLTK, or GPT
• Strong programming skills in Python
• Experience with data visualization tools
• Experience with database technologies

Bonus items:

• Experience in the use of data science to advance scientific research
• Knowledge of medical and/or scientific terminologies and ontologies

The perks and benefits

• Competitive salaries relevant to your experience level, reviewed twice yearly
• Remote team so you can live and work in Australia or NZ, as long as you can offer a 4-hour workday crossover with the AEST time zone
• Work week flexibility - Full time, part time or explore a flexible arrangement with us that best suits you and us
• Gifted time off between Christmas and New Years
• Support for parents with 14 weeks paid primary carers leave and 8 weeks paid leave for partners, available after only 6 months tenure
• Access to wellbeing services & programs to support your wellbeing
• A knowledge allowance and time so you keep learning and developing
• Monthly home allowance to set up and run your home office.

The interview process

If you are interested in this opportunity, please hit APPLY and send us through your details. We’ll be back in touch with you shortly.

Should we proceed further you can expect 3 interviews:

• Round 1: 20 min Zoom interview for us to get to know each other
• Round 2: 60 min Zoom interview diving into your technical experience and team experiences
• Round 3: 90 min Zoom interview where you’ll complete a practical exercise with some of our team members

In a hurry? We can speed this process up if needed - just let us know.

If you are excited about the opportunity to shape the future of systematic reviews and have a track record of delivering innovative solutions, please apply. We look forward to hearing from you!