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Senior Data Scientist
2 months ago
One of our top clients is hiring a
Senior Data Scientist:
Business Unit:
Compliance & Public Policy
Location:
HDQ, Vienna VA / Hybrid
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
Qualifications and Education Requirements:
• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field, or the equivalent combination of education, training and experience
• Ability to understand complex business problems and determine what aspects require optimization and articulate those aspects in a clear and concise manner
• Advanced skill in communicating actionable insights using data to technical and non-technical audiences
• Significant experience working in a dynamic, research-oriented groups with several ongoing concurrent projects
• Demonstrates advanced functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and Tableau
• Ability to manipulate raw data within visualization tools to create effective dashboards that communicate end-to-end data outcomes visually
• Advanced storytelling with data skills
• Exceptional technical writing skills
Advanced Analytics Focused
• Advanced skill in descriptive, predictive, and prescriptive analytics and modeling; demonstrated success in building models that are deployed and have made measurable business impact
• Significant experience in using two or more of the following modeling types to solve business problems: classification, regression, time series, clustering, text analytics, survival, association, optimization, reinforcement learning
• Advanced knowledge of advanced techniques such as: dimension reduction techniques, natural language processing, sentiment analysis, anomaly detection, geospatial analytics, etc.
• Demonstrates a deep understanding of the modeling lifecycle
• Advanced skill data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data models
• Advanced skill interpreting, extrapolating, and interpolating data for statistical research and modeling
• Advanced skill in Data Interpretation, Qualitative and Quantitative Analysis
• Advanced skill in Python and R
• Advanced skill in SQL and querying (able to pull/transform your own data)
• Advanced knowledge of cloud computing technologies such as: Apache Spark, Azure Data Factory, Azure DevOps, Azure ML (Machine Learning), Hadoop, Microsoft Azure, Databricks, AWS, Google Cloud
• Understanding of data models, large datasets, business/technical requirements, BI tools, statistical programming languages and libraries
• Familiar with Data Engineering concepts
• Familiar with the use of standard ETL tools and techniques
• Familiar with the concepts and application of data mapping and building requirements
• Demonstrates a deep understanding of multiple data related concepts
• Familiar with Data Integration, Data Governance and Data Warehousing
• Advanced skill in Data Management, Data Validation & Cleansing and Information Analysis
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