Covidence.org Looking for Data Scientist at New Zealand Full Time

About Covidence

Our mission is to dramatically improve lives by changing the way the world creates and uses knowledge.

Launched in 2014 Covidence is a not for profit world leading SaaS platform. Our platform enables health and science research teams to rapidly synthesize and uncover actionable insights from the mountains of research produced around the world. We do this by accelerating a research workflow called ‘systematic review,’ the gold standard for synthesizing research evidence. Many of the world’s most prestigious and innovative universities use Covidence.

The Opportunity

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

You will be the first Data Scientist at Covidence and will work within a cross functional Product & Engineering team of 15 people. The team has already launched features that use external machine learning (ML) models e.g. to drive sort orders, to classify studies. We now want you to help us build our own ML models. We’re early on this journey and are currently using MLflow to manage our experiments but we’re keen for you to help define the tools we will use over the long term.

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
• Analyze data and conduct experiments to improve the accuracy and efficiency of models
• 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 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 item: Experience in large language models
• Bonus item: Experience in the use of data science to advance scientific research
• Bonus item: Knowledge of medical and/or scientific terminologies and ontologies

The perks and benefits

• Competitive salaries relevant to your experience level
• Remote team so you can live and work anywhere as long as you can offer a 4 hour workday crossover with the AEST timezone
• Work week flexibility – FT, PT or explore a flexible arrangement with us that best suits you
• 4 weeks paid leave, an extra paid week off between Christmas and New Years Eve, and the option to purchase 3 more weeks pro rata
• Access to wellbeing services & programs
• A knowledge allowance 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 promptly.

Should we proceed further you can expect 4 interviews:

• Round 1: 30 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
• Round 4: 60 min interview with our CEO

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!