Job Title

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 OpportunityCovidence is seeking a mid to senior 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.You will be our second 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 improvementDesigning and developing state-of-the-art NLP algorithms, with a focus on orchestrating LLMs across various providers (OpenAI, Anthropic, Google, etc.) to optimize for cost, latency, and accuracy.Analyse data and conduct experiments to improve the accuracy and efficiency of modelBuild and deploy models that can be integrated into production applicationsEvaluate emerging LLM tools and frameworks to maintain a competitive edge in research automationCollaborate with leading ML practitioners in the research synthesis space to fundamentally change the way the world derives accurate insights from global research outputWhat you bring:Strong problem-solving skills with a data-driven mindset for complex research challenges.Deep hands-on experience developing LLM solutions, including prompt engineering, fine-tuning, and multi-modal API integration from different providers.Experience in LLM evaluation and benchmarking, specifically using robust and efficient frameworks to quantify model performance and factual consistency.Strong programming skills in Python with experience in deploying ML/LLM models to production applications.Experience with NLP techniques and tools for semantic analysis and information extraction.Experience in building Retrieval Augmented Generation (RAG) pipelines using vector Databases (e.g. Milvus, Pinecone, or Chroma) and efficient retrieval strategies.Experience with data visualization tools and common database technologies.Bonus:Expertise in building autonomous agentic loops using frameworks like LangGraph or CrewAI to handle multi-step reasoning tasks.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 yearlyRemote 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 zoneWork week flexibility - Full time, part time or explore a flexible arrangement with us that best suits you and usGifted time off between Christmas and New YearsSupport for parents with 14 weeks paid primary carers leave and 8 weeks paid leave for partners, available after only 6 months tenureAccess to wellbeing services & programs to support your wellbeingA knowledge allowance and time so you keep learning and developingMonthly 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 otherRound 2: 60 min Zoom interview diving into your working style, experience and motivationRound 3: 90 min Zoom interview where you''ll complete a practical exercise with some of our team membersWe don''t use AI in our screening process, please don''t use it in your application or interviews.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! #J-18808-Ljbffr