work closely with nybl to identify issues and use data to propose solutions for effective decision making
build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation
use machine learning tools and statistical techniques to produce solutions to problems
test data mining models to select the most appropriate ones for use on a project
maintain clear and coherent communication, both verbal and written, to understand data needs and report results
create clear reports that tell compelling stories about how customers or clients work with the business
assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
horizon scan to stay up to date with the latest technology, techniques and methods
conduct research from which you'll develop prototypes and proof of concepts
stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.

Experience and knowledge in statistical and data mining techniques using (e.g., python, R, SQL)
Experience and knowledge in applying advance Machine Learning techniques (e.g., Neural networks, supervised and unsupervised ML, computer vision and image processing, text analysis)
Experience and knowledge in big data analysis and management and distributed computing tools (e.g., Hadoop, Hive, Spark)
Experience and knowledge in one or more programming languages (C, C#, Java)
Experience and knowledge in web development frameworks (javascript, React, node.js)
Experience analyzing data from 3rd party providers: (e.g., Google Analytics, Site Catalyst, Facebook Insights)
Experience visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
Experience working with and creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
Excellent written and verbal communication skills for coordinating across teams.
A drive to learn and master new technologies and techniques. Willingness to learn new technology. Able to work independently on researching solutions and applying findings.

Data Scientist

Key skills