For job application, please email to BOTH firstname.lastname@example.org and email@example.comIs adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action (e.g. for data analytics, AI and ML purposes; use predictive modelling to increase and optimize customer experiences, revenue generation, and other business outcomes, etc.)
To support our product, sales, leadership and marketing teams with insights gained from analyzing company data, the ideal candidate
has strong experience using a variety of data mining/data analysis methods, building and implementing models, using/creating algorithms and creating/running simulations; mine and analyze data from company databases to drive optimization and improvement of product development, marketing, sales, network optimisation and business strategies.
Is well versed in data modelling, machine learning and AI algorithms and creating data sets for AI/ML based outcomes.
has a proven ability to drive business results with their data-based insights.
is comfortable working with a wide range of stakeholders and functional teams with a passion to discover solutions hidden in large data sets and working with stakeholders to improve business outcomes.
Strong problem solving skills with an emphasis on product development.
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.
Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, game theory, 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.
Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Coremetrics, Adwords, Crimson Hexagon, Facebook Insights, etc.
Can work with both structured and unstructured data.
Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc.
Experience in building propensity and attribution models.
A drive to learn and master new technologies and techniques.
3-7 years of experience of working with data 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:
Good to have:
Experience using web services: Redshift, S3, Spark, DigitalOcean, etc.
Experience visualizing/presenting data for stakeholders using: Periscope, alteryx, SAS, tableau, D3, ggplot, etc.
Excellent written and verbal communication skills for coordinating across teams and presenting results to non data savvy executives