Elder Research
Data Scientist
Elder Research, Arlington, Virginia, United States, 22201
Data Scientist
Location: Arlington, VA
Clearance - Must currently possess a US Government Public Trust clearance
Hybrid
Elder Research Inc. is a Data Science consulting firm specialized in providing analytic solutions to clients in Commercial and Government industries. Providing analytic solutions to hundreds of companies across numerous industries, our team enjoys a great variety in the type of work they do and exposure to a wide range of techniques and tools. We are trusted advisors to our clients, building lasting relationships and partnering as preferred analytics providers. We use a variety of programming languages and tools to create analytic solutions, often fitting within our clients' environment and needs.
Summary of Position:
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.
This position will be part of our Government Civilian Team serving Federal Civilian agencies as our primary customers.
Elder Research is a Government contractor and our positions require US Citizenship.
Essential Functions: 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 Demonstrated experience using statistical and analytical software (including but not limited to Python, R, and SQL) 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. Job Specifications/Requirements:
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. Desired Skills
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)
Elder Research, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
To be considered for this position, you must be eligible to legally obtain a US Public Trust.
Location: Arlington, VA
Clearance - Must currently possess a US Government Public Trust clearance
Hybrid
Elder Research Inc. is a Data Science consulting firm specialized in providing analytic solutions to clients in Commercial and Government industries. Providing analytic solutions to hundreds of companies across numerous industries, our team enjoys a great variety in the type of work they do and exposure to a wide range of techniques and tools. We are trusted advisors to our clients, building lasting relationships and partnering as preferred analytics providers. We use a variety of programming languages and tools to create analytic solutions, often fitting within our clients' environment and needs.
Summary of Position:
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.
This position will be part of our Government Civilian Team serving Federal Civilian agencies as our primary customers.
Elder Research is a Government contractor and our positions require US Citizenship.
Essential Functions: 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 Demonstrated experience using statistical and analytical software (including but not limited to Python, R, and SQL) 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. Job Specifications/Requirements:
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. Desired Skills
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)
Elder Research, Inc. is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability.
To be considered for this position, you must be eligible to legally obtain a US Public Trust.