Senior Applied Scientist
The world's largest asset class, debt, operates with the worst data.
Technology has revolutionized equity markets with electronic trading, quant algos and instantaneous news. However, in debt capital markets, the picture is completely different. It still behaves like it’s in the 1980s; trillions of dollars of trades are placed over the phone, news is slow, and corporate credit information is imperfect and scattered.
Our mission is to change this.
9fin's proprietary technology delivers fast and comprehensive financial, credit, legal & ESG analysis. Our clients are able to make faster, more informed decisions, win more business and most importantly, save time.
Our fast growing list of clients include 9 of the top 10 Investment Banks, leading Asset Managers, Hedge Funds and Law Firms.
The Data Science team is growing at 9fin! We are doing world-class work with ground breaking technologies to build data-driven products using machine learning, computer vision, natural language processing, speech and audio, and knowledge/data mining. We are looking for a Senior ML Applied Scientist to help us define and build our capabilities. Come and join us, you will get to build large scale machine learning systems, learn and apply the latest techniques, and work alongside other great researchers and engineers!
What you'll work on
Every day is different, but here's an example of the kind of things you'll work on:
- Drive end to end model development lifecycle, leading the team in best practices, ensuring reproducible research and well managed model delivery/deployment.
- Collaborate cross functionally to share diverse ideas, understand business problems, and elevate/mentor your teammates.
- Translate complex problems into well defined scoped bets in an internal startup style environment, dynamic and fast paced.
- Learn and apply ground-breaking research and approaches in advanced topics, iterating improvements with fail fast mentality.
- Be a proactive sharer of compelling ideas/work to the rest of the team and organisation. We want you to help lead/push the adoption of AI throughout 9fin.
This role will be a great fit if you have:
- Strong proficiency in Python, SQL, and have solid programming skills.
- Hands-on professional experience in one or more of the areas: NLP, Recommender systems, time series analysis.
- Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn, TensorFlow).
- Experience working in the full model lifecycle (incl.l experimentation, training, testing, monitoring, and deployment).
- Knowledge of AWS / GCP's machine learning infrastructure is a plus
We’re a scaling start up and we enjoy sharing our success, when the company succeeds, we always reinvest that in our people. We also offer huge amounts of responsibility, an abundance of opportunity for growth and a platform to truly excel.
Financial & Insurance
- Competitive Salary(our salary bands are benchmarked at the top end of the market)
- Equity options
- Pension (your minimum contributions are 4% with 9fin matching up to 7%)
- Private Medical Insurance
- Paid sick leave with Income Protection for long periods of illness
- Group Life Assurance
- Season Ticket Loan & Cycle to Work schemes
- 25 holiday days per year
- Local public holidays (with the ability to exchange them for alternative days)
- Hybrid working model, to allow you the flexibility to decide how, where and when you do your best work
- Work abroad for up to 3 months a year
- 1 month paid sabbatical after 5 years of service
- Enhanced parental leave & flexible working arrangements available
Training & Culture
- Professional learning and development budget
- Quarterly team socials
- Summer and Winter company social events
9fin is an equal opportunities employer
Don’t meet every single requirement? At 9fin we are dedicated to building and promoting a fair and inclusive workplace where everyone can flourish, reach their full potential and truly belong. We recognise diverse teams allow a more creative and productive environment. So, if you’re excited about this role but your experience doesn’t perfectly align with the job description, we encourage you to apply anyway. You might just be who we’re looking for - for this role, or perhaps another.