Overview:
We are seeking the services of a qualified Data Scientist to utilize their analytical, statistical, and programming skills to collect, analyze, and interpret large data sets and deliver analytics and insights (predictive, prescriptive, diagnostic, deep learning).
The ideal candidate will use these insights to develop data-driven solutions to difficult business challenges to the management team.
Responsibilities
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to data sets.
Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develop company A/B testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Develop processes and tools to monitor and analyze model performance and data accuracy.
Leverage visualisation tools to deliver graphs, tables and charts for management decision
Deliver API services for data consumption by 3rd parties and partners.
Qualification:
Bsc. in Statistics, Mathematics, Computer Science or other quantitative field
6+ years of experience manipulating data sets and building statistical models
Strong problem-solving skills with an emphasis on product development
Excellent written and verbal communication skills for coordinating across teams
A drive to learn and master new technologies and techniques
EXPERIENCE
Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets.
Experience working with and creating data architectures using AWS, Heroku and MongoDB.
Experienced using MongoDB Graph, Tableau etc
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.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
Experience using web services: Redshift, S3, Spark, DigitalOcean, MongoDB, Heroku etc.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
Experience 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 visualizing/presenting data for stakeholders using: Periscope, Business Objects, D3, ggplot, etc.
Vendease
