Job Description
Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, visualisation, ongoing deliverables, and presentations.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive understanding of data structures and metrics, advocating for changes where needed for both products development and sales activity.
Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for improved design and suggest improvements to products.
Make business recommendations (e.g. cost-benefit, forecasting, and experimental analysis) with effective presentations of findings to multiple levels of stakeholders through visualisation.
Research and develop analysis, forecasting, and optimization methods to improve the quality of Resulticks user facing products; example application areas include ads quality, search quality, end-user behavioural modelling, and live experiments.
What you will need to thrive:
MSc statistician degree in a quantitative discipline.
5 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / computational biologist / bioinformatician).
Experience with statistical software (e.g., R, Julia, MATLAB, pandas) and database languages (e.g., SQL)
ETL and scripting languages, including Perl or Python. Experience in applying technical datasets to IC mission priorities. Experience in applying computational concepts to technical targeting initiatives. Work experience in Big data environment such as Hadoop / map reduce will be an advantage.
Analytical engagements outside class work while at school can be included.
Applied experience with machine learning on large datasets.
Experience in articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience in translating analysis results into business recommendations.
Demonstrated skills in selecting the right statistical tools given a data analysis problem. Demonstrated effective written and verbal communication skills.
Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.