Mid-Level Data Scientist

Akima, LLC•Indian Head, MD

1d•Onsite

About The Position

We are seeking an experienced Mid-Level Data Scientist to apply advanced analytical, statistical, and programming techniques to complex datasets in support of data-driven decision-making and mission requirements. This position will develop and apply statistical models, machine learning algorithms, predictive data models, and data visualization techniques to identify patterns, trends, relationships, and actionable insights. To join our team of outstanding professionals, apply today! The Mid-Level Data Scientist will work with large volumes of structured and unstructured data and leverage databases, analytical methodologies, and big data technologies to support intelligence and business objectives. The ideal candidate will have strong technical and analytical skills and experience translating complex data into meaningful insights, visualizations, and intelligence support products.

Requirements

Bachelor’s degree (BA/BS) in Business, a technical field, or another related discipline from an accredited college or university is desired.
Five (5) years of relevant professional experience is desired.
Demonstrated experience with advanced data analysis, statistical modeling, and programming techniques.
Experience working with large structured and unstructured datasets.
Experience applying machine learning, data mining, predictive modeling, and quantitative analysis techniques.
Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
Experience working with databases and data management methodologies.
Knowledge of big data technologies such as Hadoop, Spark, or similar platforms.
Strong analytical, problem-solving, and critical-thinking skills.
Ability to translate complex analytical results into clear, actionable findings and visualizations.
Must hold an applicable IAT Level II certification, such as CompTIA Security+.
Active Top Secret security clearance or the ability to obtain and maintain a Top Secret clearance.

Nice To Haves

Experience supporting U.S. Government or Department of Defense programs.
Experience supporting intelligence, mission analysis, or other national security-related requirements.
Experience developing intelligence support packages, dashboards, infographics, or other analytical products.
Experience working with both structured and unstructured data sources.
Experience with advanced machine learning algorithms and statistical modeling techniques.
Experience with additional data science, programming, database, or big data technologies.

Responsibilities

Apply advanced analytical, statistical, and programming techniques to interpret complex datasets and extract meaningful insights.
Design, develop, and implement analytical models, algorithms, and statistical analyses to address business and mission challenges.
Work with large volumes of structured and unstructured data to identify patterns, trends, correlations, and relationships.
Apply machine learning and data mining techniques to analyze complex datasets and support data-driven decision-making.
Develop and utilize predictive data models and quantitative analysis techniques to evaluate targeted data sources.
Identify appropriate data sources, indicators, relationships, and methodologies to support analytical and intelligence requirements.
Leverage knowledge of databases and data management methodologies to collect, organize, analyze, and interpret information.
Develop analytical products and intelligence support packages based on identified data, trends, relationships, and findings.
Develop and support the creation of infographics, dashboards, and other data visualization products across a range of media platforms.
Utilize data visualization tools such as Tableau and Power BI to communicate complex information in a clear and meaningful manner.
Apply big data technologies, including platforms such as Hadoop and Spark, to support the processing and analysis of large datasets.
Evaluate analytical results and communicate findings, trends, and recommendations to program leadership and other stakeholders.
Collaborate with technical, analytical, program management, and customer teams to identify data requirements and develop effective analytical solutions.
Support continuous improvement of analytical methodologies, models, tools, and data products.