Machine Learning Engineer
The City, City (EC4)
£8,000 - £70,000 per annum
Machine Learning Engineer, Data Scientist, Data Science Engineer
Location: London Bridge
Salary: £70,000 - £80,000 + Equity + benefits.
They're looking for a Machine Learning Engineer to lead their Data strategy and team. As the Machine Learning Engineer you'll need to have strong Machine Learning experience, ideally along with Deep Learning, in order to mentor and train the junior-mid level Data Scientists / Machine Learning Engineers within the current team.
They are a Tech Product Company, 5 minutes walk from London Bridge station and have created a friendly, collaborative and supportive environment who hold Friday TED talks (and supply food!), have a nice pub on their doorstep and offer flexible/remote working as well as an employee share scheme, regular pay reviews, Pension scheme, quarterly dinners, birthday cakes and social events plus they're always on the lookout for creative ways to look after you and will encourage you to go to them with new idea or needs.
About the role...
- As the Machine Learning Engineer you'll report to the CTO, create deep actionable insights, visualise data, and build models for all aspects of their products. Utilising diverse data from commercial insurance, technical pricing and operational policy performance by engagement with customers and internal teams as well as lead and grow their data science expertise.
- This is an exciting and rewarding role requiring a smart, disciplined and experienced Lead Machine Learning Engineer who is statistically savvy with a very strong technical background in applying Machine Learning and data analytics techniques.
- The Lead Machine Learning Engineer role will have the potential to grow into Director of Data Science role over time.
Machine Learning Engineer key attributes:
- You have created multiple predictive models from scratch, starting from concepts to robust deployment in production. You have led all phases of Data Science projects and possess a deep understanding of all interdependencies and challenges involved around data quality, uncertainties around hypothesis validation and high expectation from the business.
- You are very hands on with various machine learning algorithms and approaches, and know the difference between good fit and bad fit. The model you produce can be used as an example for the rest of Data Science team, you lead by example and have mentored teams of data scientists and data analytics engineers in your past roles.
Machine Learning Engineer tools:
- Data wrangling and processing skills using Apache Spark (SparkSQL, SparkMlib, SparkStreaming), Hive/Pig or similar tools along with data analysis and predictive modelling
- Ability to communicate results and educate others through reports and presentations
- The ability to own data models and business team
- Experience with command-line scripting, data structures and algorithms and ability to work in a Linux environment, processing large amounts of data in a cloud environment (AWS, Google Cloud Platform)
- Knowledge in: Risk Statistical Modelling, Machine Learning and Predictive Modelling, and Data mining
- Creative approach to building test hypothesis and statistical methodology to design experiments and interpret the outcomes
If you're a Machine Learning Engineer who's keen to find out more, please apply now!
- Apache Spark (preferably with pySpark) and R (packages: dplyr, tidyR, Caret, H2O), and Python Pandas, Numpy, SciKit, programming languages (e.g. Java, Python, Ruby)
- Supervised Learning (Regression, Classification), Unsupervised (Clustering), Dimensionality Reduction, Model selection and optimisation, Feature selection, Metric selection, bootstrapping, Ensembling & Stacking methods.