Data Scientist - London

London, UK
London, UK – Data Science - London
Full-time

You will be joining the Jawbone Health Data Science team based in London in its infancy. You'll be in a unique position to help shape the team and projects we will be working on, as well as the tools and techniques we will be developing. If you are a self-starter and mathematical modeling is your utmost interest then this might be the right position for you. 

Jawbone Health is at the forefront of revolutionizing primary care for millions of patients worldwide. Combining more than 20 years of proprietary wearable technology with clinically relevant signals, Jawbone Health connects patients and physicians like never before with continuous, data-driven dialogue. This unique position of daily directed guidance stands to redefine primary care, while helping people live happier, healthier and longer.

Core Responsibilities:
Given a predictive modeling problem and a set of business constraints, select the most appropriate machine learning technique to apply to the problem
Design and implement libraries of predictive features for a variety of machine learning tasks
Develop tools and methodologies for identifying an optimal set of predictive features subject to a variety of memory and CPU constraints
Work with business owners to map business requirements into technical solutions
Perform ad hoc statistical, data mining, and machine learning analyses

keywords:  Bayesian inference, probabilistic graphic models, Bayesian nonparametric, gaussian process, expectation maximization, variational methods, HMM, MCMC, feature extraction and selection, dimensionality reduction, model construction, model validation, NoSQL, MongoDB, Cassandra, Neo4J, Matlab, Hadoop, Spark

Requirements

    • Experience with a high-level statistical modeling tools such as Python and R as well as database solutions
    • Solid understanding of generative modeling approaches and Bayesian statistics
    • Solid understand of the theory and practice of machine learning algorithms, including deep learning and ensemble techniques
    • Understand the concept of data transformation, 
    • Experience with statistical error estimation techniques such as cross-validation and the bootstrap
    • Experience developing and implementing predictive models in a product development environment

Additional Desired Skills and Qualifications

    • M.Sc (or PhD) in statistics, electrical engineering, physics or computer science
    • Background in generative modeling, signal/image processing or NLP (word2vec, node2vec) 
    • Minimum of 2 years work experience applying machine learning techniques to real business problems
    • High intellect and ability to solve extremely challenging predictive modeling problems applied to a variety of different domains
    • Ability to work independently with minimal supervision
    • Motivated by continuous learning and development, dedicated to delivering exceptional solutions
    • Excellent interpersonal, written, and verbal communication skills

Possible other Experience/Tools

    • Bayesian inference, probabilistic graphic models, Bayesian nonparametric, gaussian process, expectation maximization, variational methods, HMM, MCMC, feature extraction and selection, dimensionality reduction, model construction, model validation, NoSQL, MongoDB, Cassandra, Neo4J, Matlab, Hadoop, Spark, neural network, random forest, decision trees, support vector machine