Data Scientist -Expert - Star 1678-02

Data Scientist Expert

Day to day responsibilities include:

The Contractor shall perform end-to-end quality assurance of data feeds and data sets.

The Contractor shall provide support for data triage and assessment at the Sponsors site.

The Contractor shall identify and document areas for improvement in workflows or systems.

The Contractor shall attend regular stand-up meetings.

The Contractor shall provide input to code reviews.

The Contractor shall cross-train on existing collection tools.

The Contractor shall support building, monitoring, alerting, and reporting out (e.g. dashboards).

The Contractor shall support new use cases.

The Contractor shall research and document options for collecting or aggregating data from a variety of web based and internal Sponsor platforms.

The Contractor shall evaluate web based platforms ability to detect or deny access.

The Contractor shall make recommendations on approaches to acquire information.

The Contractor shall use appropriate tools and computer programming languages, such as Python scripts, to collect and process data from a variety of sources.

The Contractor shall use Sponsor-network APIs to programmatically access data.

The Contractor shall create, maintain, and enhance systems in support of data exploitation.

The Contractor shall create or improve custom collection scripts written in Python.

The Contractor shall create or improve scripts leveraging APIs for collection needs.

The Contractor shall automate data clean-up and conditioning of collected data.

The Contractor shall automate data management and dissemination steps.

REQUIRED SKILLS AND DEMONSTRATED EXPERIENCE

Demonstrated experience programming in Python.

Demonstrated experience performing statistical analysis, testing, and modeling using Python or R.

Demonstrated experience analyzing questions, formulating requirements, determining suitable analytic approaches, evaluating results, and communicating findings to partners and stakeholders.

Demonstrated experience working with data in a variety of structured and unstructured formats.

Demonstrated experience with a variety of database tools, such as SQL and Presto, and data lakes/S3 data.

Demonstrated experience with data visualization tools, such as notebook-based visualization libraries, especially Elasticsearch, Kibana, and Tableau.

Demonstrated ability to translate complex, technical findings into an easily understood narrative in graphical, verbal, or written form.

Demonstrated experience with AI/ML, such as natural language processing in a production environment.

HIGHLY DESIRED SKILLS AND DEMONSTRATED EXPERIENCE

Demonstrated experience programming in common compiled or interpreted languages, such as Python and R.

Demonstrated experience with data management tools, such as Hadoop, MapReduce, or similar.

Demonstrated experience with technical operations.

Demonstrated experience with technical targeting.

Demonstrated experience conducting data science using the Apache Zeppelin and Jupyter notebooks platforms and Spark/Pyspark.

Demonstrated experience collaborating with colleagues to develop customer-tailored products.