Data Scientist – Machine learning engineer (£50k – £65k)
Data Scientist/ Machine learning engineer
£50k – £65k • 2.5% – 4.0%
We’re looking for someone who is intrigued by the vastness & omnipresent yet elusive nature of flowing data. Someone who is always trying to derive value & make sense out of data in context to the vision of Pottiebee. Someone who is eager to build AI tools to automate processes that would help us build on our strengths & pinpoint our weaknesses.
Identify opportunities for leveraging company data to drive business solutions.
Mine & analyze data to drive optimization & improvement of product development, marketing techniques & business strategies.
Assess the effectiveness & accuracy of new data sources & data gathering techniques.
Develop custom data models & algorithms to apply to data sets.
Use predictive modeling to increase & optimize UX, revenue generation, ad targeting & other business outcomes.
Develop A/B testing frameworks for specific use flows & test model quality.
Coordinate with different teams to implement models & monitor outcomes.
Develop processes & tools to monitor & analyze model performance and data accuracy.
Qualifications:Strong problem solving skills with an emphasis on product development.
Experience in using statistical computer languages (R, Python, SLQ, etc.) to manipulate data & draw insights from large data sets.
Experience working with & creating data architectures.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) & their real-world advantages & drawbacks.
Knowledge of advanced statistical techniques & concepts (regression, properties of distributions, statistical tests, proper usage, etc.) & experience with mobile applications.
Good written & verbal communication skills for coordinating across teams.
A drive to learn & master new technologies & techniques.
We’re looking for someone with 5+ years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools:
Coding knowledge & experience with several languages: C, C++, Java
Knowledge and experience in statistical & data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Experience in querying databases & using statistical computer languages: R, Python, SLQ, etc.
Experience in using web services: Redshift, S3, Spark, DigitalOcean, etc.
Experience in creating & using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Experience in analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience in visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.