A successful and fast-growing fin-tech start-up is looking to hire several experienced Data Scientists who have a breadth of experience across designing and implementing statistical models and machine learning algorithms to solve some very challenging problems.
This alternative investment manager start-up uses a range of artificial intelligence techniques including NLP, machine learning and deep learning to make better investment decisions.
Are you experienced, ambitious and an incredibly passionate problem solver, who likes to get stuck in, work with unstructured data and get your hands dirty to build some excellent products alongside a very talented team of data scientists and engineers (ex Facebook/Google)? If so, this could be for you.
- Working for a leading niche fin-tech start-up
- Working alongside a very talented team of data scientists and engineers (ex Facebook & Google)
- Salary £80k - £130k plus equity and bonus
About the role
Your primary role will be to work with data, design features and implement machine learning algorithms while working within the data science team. This involves data exploration and lots of fun discussions about stats. This will certainly suit someone who is solution-focused, proactive and can deliver high quality outputs to tight deadlines.
- Working closely with the rest of the data science team to design and implement machine learning algorithms, involving a lot of feature engineering
- Implementing data pipelines and machine learning algorithms, mainly using panads, SciPy, SKlearn and some Spark. Most of the work is in Python but knowing Scala would be an advantage
- Contributing to the design and overall architecture of the system. They are intent on solving problems permanently, not just putting on band aids
- Designing and implementing APIs
- Leading, mentoring and assisting junior members of the team
- MSc or PhD in Engineering, Computer Science, Mathematics etc.
- Experience in Python, NumPy, SciPy and pandas is essential
- Experience in Time Series data and particular Financial Data is highly advantageous
- Experience in Spark and other big data technologies is beneficial
- Familiarity with cloud-based environments such as AWS is beneficial
- Machine Learning
- Time Series Analysis
- Data Science