60 applicants

Company

Original Job Post

Tential Solutions · 2 days ago

Sr. Data Scientist

Vienna, VA

Contract

Hybrid

Senior Level

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Growth Opportunities

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Responsibilities

Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive, predictive, and prescriptive analytics and modeling

Leverage a broad set of modern technologies – including Python, R, and Spark to analyze and gain insights within large data sets

Manage, architect, and analyze big data in order to build data-driven insights and high-impact data models

Evaluate model design and performance and perform champion/challenger development. Analyze model input data, assumptions, and overall methodology.

Using statistical practices, analyze current and historical data to make predictions, identify risks, and opportunities, enabling better decisions on planned/future events

Provide analytics insights and solutions to solve complex business problems

Apply business knowledge and advanced statistical modeling techniques when building data structures and tools

Collaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic-based solutions from design to deployment

Examine data from multiple sources and share insights with leadership and stakeholders

Transform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision-making

Point of contact between the data analyst/data engineer and the project/functional analytics leads

Develop and maintain an understanding of relevant industry standards, best practices, business processes, and technology used in modeling and within the financial services industry

Identify improvements to the way in which analytics service the entire function

Recognize potential issues and risks during the analytics project implementation and suggest mitigation strategies

Prepare project deliverables that are valued by the business and present them in such a manner that they are easily understood by project stakeholders

Perform other duties as assigned

Assess new and existing model’s overall fit/suitability with its intended use and purpose

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data VisualizationAdvanced AnalyticsModeling TechniquesData TechniquesProgrammingCloud ComputingData ConceptsData ManagementProblem-SolvingCommunicationResearch ExperienceTechnical WritingStatisticsMathematicsComputer scienceAgileSafeProject managementDelivery excellenceRequirements management

Required

Candidates are required to be legally authorized to work in the United States without a sponsoring employer indefinitely. At this time we can only accept the following: US Citizens, GC EAD, GC Holder, TN Visa.

Must be able to work a W2 Contract (NO C2C arrangements).

Education: Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or another quantitative field, or an equivalent combination of education, training, and experience.

Problem-Solving: Ability to understand complex business problems, identify optimization opportunities, and articulate them clearly.

Communication: Advanced skill in communicating actionable insights using data to both technical and non-technical audiences.

Research Experience: Significant experience working in dynamic, research-oriented groups with multiple concurrent projects.

Data Visualization: Advanced knowledge of data visualization libraries such as matplotlib or ggplot2 and other tools like Microsoft Power BI and Tableau.

Technical Writing: Exceptional technical writing skills.

Advanced Analytics: Advanced skills in descriptive, predictive, and prescriptive analytics and modeling, with demonstrated success in deploying impactful models.

Modeling Techniques: Experience with various modeling types, including classification, regression, time series, clustering, text analytics, survival, association, optimization, and reinforcement learning.

Data Techniques: Advanced knowledge of techniques like dimension reduction, natural language processing, sentiment analysis, anomaly detection, and geospatial analytics.

Data Skills: Advanced skills in data mining, wrangling, transformation, interpretation, qualitative and quantitative analysis, and statistical research.

Programming: Proficiency in Python, R, SQL, and querying.

Cloud Computing: Knowledge of cloud computing technologies such as Apache Spark, Azure Data Factory, Azure DevOps, Azure ML, Hadoop, Microsoft Azure, Databricks, AWS, and Google Cloud.

Data Concepts: Familiarity with data engineering, ETL tools, data mapping, data integration, data governance, and data warehousing.

Data Management: Advanced skills in data management, validation, cleansing, and information analysis.

Preferred

Education: Doctoral degree in Statistics, Mathematics, Computer Science, Engineering, or another quantitative field.

Project Management: Familiarity with project management concepts and frameworks such as Agile (SAFE), communication strategy, management, delivery excellence, and requirements management.