Data Scientist

Elder Research-posted 2 days ago

Full-time • Mid Level

Hybrid • Arlington, VA

101-250 employees

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As a Data Scientist , you will work directly with clients, managers, and technical staff to understand business needs, develop technical plans, and deliver data-driven analytical solutions that solve client problems. You will primarily create and deploy predictive models from a wide variety of data sources and types using the latest mathematical and statistical methods and other emerging technologies.

Exploring, cleaning, and wrangling data to provide value-added insights and identify business problems suitable for Data Science solutions
Experience across the spectrum of design, develop, test, and implement quantitative and qualitative Data Science solutions that are modular, maintainable, resilient to industry shifts, and platform-agnostic
Analyzing events across government, financial industries, law enforcement, and other similar data environments prioritizing them by compliance and business risk and displaying the results in evidence-driven monitoring and decision support tools.
Experience in quantitative statistical approaches to anomaly detection to identify non-compliance risk, fraud, and cyber threats using data discovery, predictive analytics, trend analysis, assessment, and appropriate contemporary and emerging analytical techniques.
Ability to conduct rigorous quantitative data analysis on very large quantitative data sets to develop insights and develop actionable recommendations due to previous experience developing strategies, performing assessments, gap analyses, and making actionable recommendations
Contribute to meetings and discussions with clients and co-workers to refine understanding of the business problem at hand
Trying different predictive modeling approaches to identify the best fit for a given set of business understanding, available data, and project timeline
Writing modular, understandable, re-usable code within an iterative development process that includes team-based code review, client discussions, and end-user training
Applying statistical tests for robustness, sensitivity, and significance to test and validate supervised and unsupervised models
Preparing presentations, writing reports (technical and non-technical), and working to communicate technical results to clients with varying levels of analytic sophistication
Ability to work autonomously in a collaborative, dynamic, cross-functional environment
Demonstrated business savvy with solid interpersonal and communication skills (written and verbal).
Experience with design and delivery capabilities with proficiency in gathering requirements and translating business requirements into technical specification.

Must have a IRS Public Trust w/a Full Background Investigation
Bachelor of Science degree in a relevant field (statistics, business, computer science, economics, mathematics, analytics, data science, social sciences, etc.,)
Demonstrated experience using statistical and analytical software (including but not limited to Python, R, and SQL)

Bachelor of Science degree in a relevant field (statistics, business, computer science, economics, mathematics, analytics, data science, social sciences, etc.,)
1+ years of experience in data science, data analytics, or a related technical field
Prior computer programming experience, preferably in a language such as Python or R
Experience with data exploration, data munging, data wrangling, and model development in R or Python
Experience using version control (e.g. git, svn, Mercurial) and collaborative
Basic understanding of relational database structure and SQL
Humble and willing to learn, teach, and share ideas
Experience engaging and interacting with clients, stakeholders and subject matter experts (SMEs) to understand, gather and document requirements
Comfortable learning new things and working outside of your comfort zone
Technical mindset you are not afraid of math!
Must currently possess a Public Trust clearance
Travel to and work on-site at clients both local and non-local. Number of days at client site vary depending on project requirements.
Advanced degree (MS or PhD) in a relevant field (e.g., statistics, computer science, business, mathematics, analytics, data science, engineering, physics, social sciences, management information systems, or decision science, etc.,)
Programming techniques (e.g. pair programming, code reviews)
Experience with containerization and environment management (venv or conda)
Experience with Natural Language Processing (NLP) and advanced text mining techniques
Experience with graph analytics and network analysis
Experience with one or more technologies such as R Shiny, Databricks, AWS, Azure
Experience applying robust, established and emerging quantitative & statistical techniques, knowledgeable on the underlying theoretical and architectural frameworks in the fields of applied analytics, and statistical analysis to include: sampling considerations & survey design like construct validity, measurement bias, as well as internal & external validity, statistical weighting techniques, approaches to outlier and missing data, and exploratory data analysis, cross-sectional analysis, and longitudinal forecasting
Experience implementing data science processes in a remote, austere environment to include using bash
Experience with business intelligence and data visualization platforms (Power BI, Tableau, etc.,)
Understanding of the data analytics lifecycle (e.g. CRISP-DM)

Competitive Salary and Benefits
Job Stability
People-Focused Culture
opportunities for professional growth and advancement
parental, bereavement, and PTO policies

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