Collaboratively identify opportunities to integrate data into decision processes. With your help decisions should take less time, allocate resources more effectively, incorporate more sources of information, make decisions more transparent, and more explicitly consider alternative courses of action.
Work with business intelligence and product analysts to translate regular work processes like reporting or marketing campaign evaluations into clear, outlined processes. Then convert those processes into algorithmic applications.
Consistently raise data and analytic standards by improving and developing new statistical methods and algorithms. Educate stakeholders (including other data science teams and analysts across the company) as to their use.
Ensure that the various databases and data pipelines across the company are as accessible and usable as possible for stakeholders and decision makers at every level.
Skilled in manipulating and analyzing complex, high-volume, high-dimensionality data from varying sources.
Comfortable communicating and working with non-technical partners and colleagues to translate tasks done by humans into tasks that can be done by algorithms. Capable of implementing your designs as reusable and scalable programs and applications. Familiarity with Microservice Architecture is a plus.
Fluency with at least one scripting language like Python, Ruby or Scala. You should be able to build Django apps and be comfortable with the idea of using Python libraries (or equivalent) like Celery or Luigi.
Knowledge of non-relational databases like MongoDB or Hadoop, query tools (e.g. Hive or Pig) and tools for distributed computation (e.g. Spark) are highly desirable.
Should value simple solutions, write concise code, lead with tests, and believe in devops.