Data Scientist at Applied Engineering Management Corporation in Salt Lake City, Utah

Job Description:

Job Description
This position provides data science support and services to the Federal Highway Administration (FHWA),
the Transportation Research Board (TRB) (part of the National Academy of Sciences and Engineering), and
state departments of transportation in leveraging a wide variety of data to deliver improved
transportation services and increased safety on our nations roadways.
Job Duties
1. Apply modern data analysis and management techniques to transform data from transportation
agencies and their partners into actionable information:
Assess and document current data processing and visualization systems of transportation agencies.
Assess and document the quality and veracity of transportation data and associated data
products, from raw data to key performance indicators (KPIs), charts, and dashboards.
Identify the data needs of transportation agencies (federal, state, local) and define data analysis
workflow and visualization requirements to satisfy these needs.
Develop, deploy, and maintain real-time and batch data analysis workflows using AWS, GCP,
Microsoft Azure, or other platforms in support of both FHWA and state DOT projects.
Research, test, and develop real-time geotemporal conflation techniques to integrate disparate
datasets from transportation agencies, private industry (e.g., freight providers, third-party data
providers), and crowdsourcing/social media sources.
Develop, deploy, and maintain data analysis workflows using natural language processing (NLP),
machine learning, fuzzy matching, and other techniques to retrieve useful information from
unstructured data.
Develop, deploy, and maintain custom dashboards, reports, and visualizations using off-the-
shelf, cloud-based data visualization tools and libraries.
Understand and apply data encryption and obfuscation techniques to hide Personally Identifiable
Information (PII) in datasets and conform to various state and federal privacy policies.
2. Support research efforts, client relationships, and business development:
Participate in and contribute to meetings/discussions with state and federal clients.
Lead or contribute to literature reviews, transportation stakeholder workshops (virtual and in-
person), and information-gathering interviews with transportation agencies. Document
discussions during these events.
Clearly explain and discuss modern data analysis and visualization techniques and concepts to
federal and state customers, tailoring each discussion to their level of technical understanding.
Support the preparation of technical memos and briefings, technical and research reports, and
guidance documents.
Present or support the presentation of project findings/outcomes to clients, partner and peer
agencies, and the broader transportation industry.
Support business development efforts through the development of proposals and technical
briefings.

Desired Skills
Experience with scripting languages such as Python and R.
Experience using data science tools and libraries such as Pandas, NLTK, scikit-learn, Rapids,
Elasticsearch, or others.
Experience developing visualizations using multiple data visualization platforms (e.g., Power BI,
Tableau, Kibana, etc.).
Experience developing data processing workflows with cloud computing services such as AWS,
GCP, or Microsoft Azure.
Experience working with traditional and modern data files formats such as CSV, JSON, XML,
Apache Avro, and Apache Parquet.
Experience with serverless programming, parallel computing, regular expressions, machine
learning (e.g., NLP, image recognition)
Experience working with both traditional and modern spatial datasets (e.g., Shapefile, geohash, etc.).
Experience with processing unstructured data such as text, images, and video.
Experience with merging/integrating heterogenous datasets.
Experience with feature selection/engineering, including mapping unstructured data to tabular
dataset features.
Experience developing and optimizing classifiers using methods such as logistic regression,
decision trees, support vector machines, or deep learning.
Strong applied mathematics and statistics skills, such as distributions, statistical testing,
regression, etc.
Experience with change management software such as Git.
Some understanding of transportation-related data is preferred.
Minimum Qualifications
Masters Degree or equivalent combination of education and experience.
5+ years of software development / data analysis / engineering experience.
Must possess or be able to obtain a Public Trust (NACI).
Software expertise required in Python programming and Python packages (Scikit-Learn, Numpy,
Pandas), SaaS suite of at least one cloud provider (AWS, GCP, or MS Azure), and one or more
visualization platforms such as Tableau, Google Data Studio, OmniSci, etc.
Desire to join a small team of experts working on innovative projects towards the improvement of
transportation services and roadway safety nationwide.
Ability to quickly learn new technologies to complete a wide variety of tasks across novel projects.
Strong written and oral communication skills and data-oriented personality.
Ability to manage time effectively to complete assignments on time across multiple ongoing
projects with minimal guidance or supervision.