Turing Talent Tech Careers Programme - Enveda data scientist
About Turing Talent Programme
The Turing Talent Tech Careers Programme is a first-of-its-kind career empowerment programme for ambitious individuals in the technology sector. We have partnered up with Enveda to offer a data scientist role.
Through our programme, capture the added benefits of leadership development training, mentorship, and international peer network on top of your full time job with Enveda.
At Enveda, we're re-imagining the roots of medicine with technology. Our inability to model the vast complexity of the human body and the infinite variables of the real world has led to more than 90% of drugs failing in clinical testing - so instead of depending on inbred mice or cells grown on plastic like everyone else, we're hunting for active molecules from plants that have been used by our ancestors for 1000s of years (and continue to be used by hundreds of millions today). We're endlessly optimistic about the resilience of these medicinal systems over millennia and are excited to unearth their potential at the most exciting time for technology in human history (see why here, here, here, and here just for a start). Using AI to prioritize potential drugs from 1000s of clinically used plants and precision AgTech to engineer their production, we're aiming to go from the lab to clinical trials with 3 new drugs in the next 5 years. Long-term, we will deliver multiple FDA approved medicines at a fraction of today's (unsustainable) R&D costs and emerge as the much-awaited pioneers in the "Reverse Translation" of human experience to validated drugs.
More details about Enveda here.
What will you be doing
- Create a knowledge graph of the world’s information on natural medicines to make it computable
- Develop new graph-based machine learning algorithms or applying state of the art techniques to mine insight from our biological networks
- Create predictive models to identify the most interesting hypotheses to pursue in the lab
- Design statistical models to predict best drug candidates and combinations from a mixture of potentially active phytochemicals
- Work hand-in-hand with an experimental laboratory team and a bioinformatics team to analyze streams of cutting edge biological datasets to constantly improve our predictive power
- Get in on the ground floor of a rapidly growing venture-backed US startup backed by top Angels and VCs
- Be a co-owner of Enveda’s mission and vision, with generous equity compensation
- Work remotely, with a headquarter in SF for when you want company!
- An aspiring Data Scientist that is, first and foremost, passionate about applying technology to make life-changing drugs
- Have an advanced degree in Computer Science or a related field
- Have a background in data science or have worked with a large amount of data
- Have experience building research prototypes or MVPs in an academic or industry setting
- Have experience working with a programming language like Python
- Have some knowledge of modern tools for ML such as TensorFlow, PyTorch, PyTorch Geometry, or PySpark
- Ability to think big-picture and handle the minutiae simultaneously
- Demonstrated desire for continuous learning and improvement
- Strong communication
- Have some background in biology or chemistry (ideally)
- Have worked with graph-based data structures
- Have experience with using and deploying the latest graph algorithms and predictive models (GNN’s, link prediction and so on..)
- £48k to £70k
About Turing Talent Programme training:
Turing Talent Programme will kick off with a 2 to 4 week intensive bootcamp training that covers technical skills and soft skills. The technical skills will include those that specifically correspond to this placement with Deloitte, with a focus on software engineering. You will dive deeper into fullstack languages and frameworks, and how to apply this knowledge in your new role with DFA. ElasticSearch, AWS, and JIRA will all be part of the training.
Turing Talent is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.