Top Secret Sr. Data Scientist Engineer

Job description

Job Description
We are seeking a Senior Data Scientist Engineer to join our clients innovative team in Ashburn, VA.

The strongest applicants will offer multiple years of experience in highly dynamic, threat/risk driven operating environments.

They will also have a proven track record of delivering production ready decision support tools and applications employed in the field and by mission-support entities.

Further, highly competitive applicants will have a demonstrated capacity to work closely and collaboratively with mission stakeholders; respond to emergent, mission-driven changes in priorities and expected outcomes; and apply new and emerging tools and techniques.

Responsibilities include but are not limited to:

- Perform hands-on analysis and modeling involving the creation of intervention hypotheses and experiments, assessment of data needs and available sources, determination of optimal analytical approaches, performance of exploratory data analysis, and feature generation (e.g., identification, derivation, aggregation).
- Collaborate with mission stakeholders to define, frame, and scope mission challenges where big data interventions may offer important mitigations and develop robust project plans with key milestones, detailed deliverables, robust work tracking protocols, and risk mitigation strategies.
- Demonstrate proficiency in extracting, cleaning, and transforming customers transactional and mission data associated within an identified problem space to build predictive models as well as develop appropriate supporting documentation.
- Leverage knowledge of a variety of statistical and machine learning techniques and methods to define and develop programming algorithms; train, evaluate, and deploy predictive analytics models that directly inform mission decisions.
- Participate in projects including those intended to identify patterns and/or anomalies in large datasets; perform automated text/data classification and categorization as well as entity recognition, resolution and extraction; and named entity matching.
-Brief project management, technical design, and outcomes to both technical and non-technical audiences including senior government stakeholders throughout the model development/project lifecycle through written as well as in-person reporting.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day.

We are an equal opportunity/affirmative action employer that believes everyone matters.

Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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Skills and Requirements
- Undergraduate degree in mathematics, statistics, computer science/engineering, or other related technical fields and 7 plus years equivalent practical experience.
- Experience in developing machine learning models and applying advanced analytics solutions to solve complex business problems..
- Experience with programming languages including R, Python, Scala, Java, and proficiency with SQL programming.
- Experience constructing and executing queries to extract data in support of EDA and model development.
- Proficiency with statistical software packages including SAS, SPSS Modeler, R, WEKA, or equivalent.
- Experience with pattern recognition and extraction, automated classification, and categorization.
- Experience with entity resolution (e.g., record linking, named entity matching, deduplication/ disambiguation).
- Experience with unsupervised and supervised machine learning techniques and methods.
- Experience performing data mining, analysis, and training set construction.
- Experience with supervised machine learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc.
-Experience with unsupervised machine learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc.

- Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI).
- Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop).
- Master’s degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.

Required Skill Profession

Other General