Associate Data Scientist

at  ANSER

OVERVIEW:

ANSER enhances national and homeland security by strengthening public institutions. We provide thought leadership for complex issues through independent analysis and we deliver practical, useful solutions. ANSER values collaboration, integrity, and initiative and we are client focused in all that we do. Because we were established for the purpose of public service and not for profit, we measure our success in the impact of our service.

POSITION OVERVIEW:

As a data scientist, you can turn complex data sets into useful information to solve global challenges.

REQUIRED SKILLS:

• Possess an active TS/SCI security clearance
• Possess active CI Polygraph
• 3+ years of experience with data science and BA or BS degree
• Experience with using scripting languages to conduct common data analysis tasks for exploration, conditioning, and advanced analytics
• Knowledge of visual programming or object-oriented modeling workflows to automate data acquisition
• Ability to manipulate data from multiple structured and unstructured data sources
• Ability to identify and appropriately evaluate a wide range of existing methods, models and algorithms in familiar domains for a variety of mission driven problems while recognizing the capabilities and limitations of each method.
• Demonstrated strong writing and oral communication skills.
• Ability to work independently

DESIRED SKILLS:

• Bachelor’s or Master’s degree in a field relevant to data science, data analytics, and/or data visualization.
• Experience with Apache Hadoop, HUE, Hive, Pig, Spark, Elasticsearch, Kibana, or Tableau
• Knowledge of programming languages, including Java, Python, R, or SQL
• Experience with using JEMA
• Experience with GEOINT domain including geospatial intelligence or remote sensing, GEOINT databases, including GIMS, BVI, or CRATE, and ABI and multi-INT fusion

• Use leadership and analytical skills to improve GEOINT data understanding.
• Work closely with your customer to understand their questions and needs, and then evaluate their data-rich environment to find the pieces of their information puzzle.
• Mentor teammates, develop algorithms, write scripts, build predictive analytics, use automation, and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help senior leadership make informed decisions.
• Provide your customer with a deep understanding of their data, what it all means, and how they can use it.