Senior Database Architect (URGENT)

Overview

Each day U.S. Customs and Border Protection (CBP) oversees the massive flow of people, capital, and products that enter and depart the United States via air, land, sea, and cyberspace. The volume and complexity of both physical and virtual border crossings require the application of solutions to promote efficient trade and travel. Further, effective solutions help CBP ensure the movement of people, capital, and products is legal, safe, and secure.

In response to this challenge, Adtech, as a trusted mission partner of CBP, seeks capable, qualified, and versatile data scientists to help lead the development and delivery of high-quality predictive modelling solutions.

Within three - six months of joining the project, data scientists will be expected to:

•Lead and 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 CBP 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.

•Execute 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.

Qualifications

Education:

•Bachelor's Degree (required) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience.

Required Qualifications

•7-12 years of relevant experience

•Experience in applying advanced analytics solutions to solve complex business problems

•Experience with programming languages including: R, Python, JavaScript, Visual Basic

•Experience with creating VBA applications and macros to structure, manage, and wrangle key datasets

•Experience with core data science libraries - Pandas, NumPy, Matplotlib, Plotly, etc.

•Experience with Anaconda distribution of Python for package management and deployment

•Familiarity with command-line shell programming (Powershell, cmd, etc.)

•Proficiency with SQL programming

•Familiarity with RESTful APIs, web scraping, and processing unstructured data

•Knowledge of visualization and presentation techniques including Tableau, Power BI, Jupyter Notebooks, etc.

•Knowledge of cloud technologies such as AWS or Google

•Proficiency using git for version control, collaboration, and code review

•Familiarity with software organization tools and frameworks (Docker, virtual environments, etc.)

•Experience with engineering and development collaboration tools such as Jira and Confluence.

•Experience with Natural Language Processing (NLP), computational linguistics, Entity extraction, named entity recognition (NER), name matching, disambiguation,).

•Experience constructing and executing queries to extract data in support of EDA and model development

•Experience with unsupervised and supervised machine learning techniques and methods

•Experience working with large-scale (e.g., terabyte and petabyte) unstructured and structured data sets and databases

•Experience performing data mining, analysis, and training set construction

Desired Qualifications

•Proficiency with Unsupervised Machine Learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc.

•Proficiency 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 pattern recognition and extraction, automated classification, and categorization

•Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/ disambiguation)

•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

•Active Top Secret

Clearance:

Selected applicants must be a US Citizen and able to obtain and maintain a U.S. Customs and Border Protection (CBP) suitability.