Mid-Level Data Analyst

Akima, LLC•Indian Head, MD

1d•Onsite

About The Position

AMO is looking for a Mid-Level Data Analyst to work in Indian Head, MD. The Mid-Level Data Analyst supports data-driven analysis, operations research, software integration and testing, and advanced analytics efforts. This role applies statistical, mathematical, programming, and data science techniques to analyze complex information, support analytics objectives, and develop meaningful insights. The position requires hands-on experience with data analysis tools, programming languages, databases, and analytical methodologies.

Requirements

An Associate’s degree (AA/AS) and four (4) additional years of related experience may be substituted for the Bachelor’s degree.
Seven (7) years of experience in operations research is required.
Demonstrated experience applying statistical and operations research methods and tools.
Experience with data analysis, data science, data mining, statistics, or advanced analytics.
Experience with software integration and/or testing, including test plans and test scripts.
Experience using scripting languages such as Python and R.
Experience working with data science and advanced analytics packages and tools.
Experience with SQL and/or NoSQL databases.
Experience with APIs, ETL pipelines, Web Application Servers, and/or Search Index technologies.
Experience using tools such as Jupyter Notebook, Pandas, NumPy, and Requests.
Ability to apply mathematical and statistical concepts to complex analytical problems.
Experience using spreadsheets for data manipulation, analysis, and visualization.
Active Secret security clearance or the ability to obtain and maintain a Secret clearance.

Nice To Haves

Relevant industry certification in data analytics, cloud technologies, cybersecurity, or related technical disciplines.
Experience with graph algorithms and advanced data science methodologies.
Experience developing or supporting data-driven applications and analytical solutions.
Experience with complex datasets and integrating data from multiple sources.
Experience supporting U.S. Government, Department of Defense, or other federal programs.
CompTIA Cloud Essentials
Microsoft Technical Associate (MTA)
Certificate of Cloud Security Knowledge (CCSK)
CompTIA A+
CompTIA Security+
EMC Data Science Associate (EMCDSA)
Cloudera Certified Data Scientist (CCDH)
Certified Apache Hadoop Developer (HCAHD), Hortonworks
Certified Information Systems Security Professional (CISSP)
Certified Cloud Professional (CCP), Cloudera
Microsoft Certified Professional Developer (MCPD)
Microsoft Certified Solutions Developer (MCSD)
Microsoft Certified Solutions Expert (MCSE)
Private Cloud
Certified Administrator for Apache Hadoop (CCAH), Cloudera

Responsibilities

Perform data analysis, data mining, statistical analysis, and operations research to support analytics objectives.
Support software integration and testing activities, including analyzing, developing, and implementing test plans and test scripts.
Use scripting languages such as Python and R to perform data analysis and advanced analytics.
Apply data science packages, tools, and methodologies commonly used for advanced analytics.
Apply statistical methods, operations research techniques, and analytical tools to evaluate data and support decision-making.
Work with structured and unstructured data using technologies such as Structured Query Language (SQL) and Non-Structured Query Language (NoSQL).
Build and support Application Programming Interfaces (APIs) and Extract, Transform, and Load (ETL) pipelines.
Work with Web Application Servers and Search Index technologies as applicable to data integration and analytics efforts.
Apply data science, data mining, statistical, and graph algorithm techniques to support analytical requirements.
Develop and use analytical solutions with tools and technologies such as Python, Jupyter Notebook, Pandas, NumPy, and Requests.
Apply complex mathematical and statistical concepts to analyze data and solve operational and analytical problems.
Use spreadsheets and related tools for data manipulation, analysis, and visualization.
Support the development, testing, validation, and documentation of analytical solutions and data-driven products.
Collaborate with technical and analytical teams to identify data sources, evaluate information, and support project objectives.