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Lead Data/Machine Learning Scientist

17 Leathermarket Street, London SE13HN

The role

Developing products that solve real problems for our customers is at the heart of everything we do, and we’re on the hunt for an exceptional Lead Data/ML Scientist for our Quest products which are changing the game in commercial insurance.

Reporting to our CTO, the Lead Data/ML Scientist will proactively ask questions, be highly structured, inquisitive and detail oriented, create deep actionable insights, visualise data, and build models for all aspects of our products. Utilising diverse data from commercial insurance, technical pricing and operational policy performance by engagement with our customers and internal teams, you will help lead and grow our data science expertise in both London and Delhi.

This is an exciting and rewarding role requiring a smart, disciplined and experienced Lead Data and ML Scientist who is statistically savvy with a very strong technical background in applying Machine Learning and data analytics techniques.

The Lead Data/ML Scientist role will have the potential to grow into Director of Data Science role over time.

Key responsibilities

  • Analyse and model both structured and unstructured data using advanced statistical methods and implement algorithms and software needed to perform analyses
  • Perform exploratory data analysis, generate and test working hypotheses (A/B tests, Bayesian methods), prepare and analyse historical data and identify patterns and insights
  • Design statistic experiments, formulate test hypotheses and validate them on the statistical grounds.
  • Design and Perform full end to end Machine Learning projects including: Data Ingest, EDA, Data Cleansing, Data Pre-processing, Machine Learning Algorithm selection, Data feature creation and ranking, creating and training predictive models.
  • Explain and present the status and roadmap of the Data Science team to a less technical audience (Sr. Management or executives) in a simple and understandable way. 


You...super smart, versatile, innovative

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, and you lead by example and have mentored teams of data scientists and data analytics engineers in your past roles.


Key attributes:

  • 5 years + of professional experience working as a Data/ML Scientist, preferably gained within Insurance, Financial Services or Risk Management
  • Formal Statistical Qualifications from an accredited university in Computer Science, Statistics, Mathematics, Engineering, Bioinformatics, Physics, Operations Research, or related fields
  • Strong data wrangling and processing skills using Apache Spark (SparkSQL, SparkMlib, SparkStreaming), Hive/Pig or similar tools along with proficiency in data analysis and predictive modelling
  • Proven ability to communicate results and educate others through reports and presentations as well as other knowledge sharing techniques
  • Very good interpersonal skills and ability to work closely with both the engineering team to own data models and business team to help them constantly improve the business value proposition
  • 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)
  • Strong knowledge in the following fields: 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


Tools:

  • 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.


Nice to have:

  • Ability to implement, maintain, and troubleshoot big data infrastructure, such as distributed processing paradigms, stream processing and databases such as Hadoop, Spark, SQL and Solr
  • Experience with Data Visualisations tools and techniques. Experience with Big Data would be a great asset! 
  • Understanding of Insurance related risk modelling and underwriting processes. Track record of working with cluster computing and distributed systems
  • Neural network and deep learning (TensorFlow, Keras, PyTorch)
  • 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)


Benefits

As well as the opportunity to work on projects that you enjoy in an environment you’ll love, we look after our team members at Concirrus. Here are some of our perks:

  • Employee share scheme so you get to own a piece of the pie
  • We pay competitively with regular pay reviews
  • Loft office a stone’s throw from the culinary delights of Borough Market, and with a pub literally on our doorstep. The office is located within the London Leathermarket where we have access to facilities such as: on-site café/bar, bicycle storage and shower rooms
  • Coffee and snacks are all on hand in the office to keep you fuelled
  • Friday FED talks – like TED talks, but you get fed (on us)
  • Quarterly dinners, birthday cakes and social events
  • Pension scheme – generous matched contribution
  • Plus, we’re always on the lookout for creative ways to look after our employees and encourage them to come to us when they have an idea or needs

If this sounds like you - please click 'apply for this post' and submit your CV and cover letter. We look forward to hearing from you!

Posted: 3rd Aug, 2018