Dice
Data Scientist-Vienna,Virginia-Hybrid
Dice, Vienna, Virginia, United States, 22184
Data ScientistLocation:
Vienna, Virginia-HybridDuration:
6+ MonthsJob Description:
Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission-critical decision-making for Compliance-Complaints. Understand business needs and identify opportunities for improvements to products, services, and processes to meet business objectives through the use of cutting-edge data science. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Individual contributor and mentor to junior staff.Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive, predictive, and prescriptive analytics and modelingLeverage a broad set of modern technologies including Python, R, and Spark to analyze and gain insights within large data setsManage, architect, and analyze big data to build data-driven insights and high-impact data modelsEvaluate 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 eventsProvide analytics insights and solutions to solve complex business problemsApply business knowledge and advanced statistical modeling techniques when building data structures and toolsCollaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic-based solutions from design to deploymentExamine data from multiple sources and share insights with leadership and stakeholdersTransform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision-makingPoint of contact between the data analyst/data engineer and the project/functional analytics leadsDevelop and maintain an understanding of relevant industry standards, best practices, business processes, and technology used in modeling and within the financial services industryIdentify improvements to the way in which analytics service the entire functionRecognize potential issues and risks during the analytics project implementation and suggest mitigation strategiesPrepare project deliverables that are valued by the business and present them in such a manner that they are easily understood by project stakeholdersAssess new and existing model's overall fit/suitability with its intended use and purposeMinimum 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 experienceAbility to understand complex business problems and determine what aspects require optimization and articulate those aspects in a clear and concise mannerAdvanced skill in communicating actionable insights using data to technical and non-technical audiencesSignificant experience working in dynamic, research-oriented groups with several ongoing concurrent projectsDemonstrates advanced functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and TableauAbility to manipulate raw data within visualization tools to create effective dashboards that communicate end-to-end data outcomes visuallyAdvanced storytelling with data skillsExceptional technical writing skillsAdvanced skill in descriptive, predictive, and prescriptive analytics and modeling; demonstrated success in building models that are deployed and have made measurable business impactSignificant 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 learningAdvanced 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 lifecycleAdvanced skill data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data modelsAdvanced skill interpreting, extrapolating, and interpolating data for statistical research and modelingAdvanced skill in Data Interpretation, Qualitative and Quantitative AnalysisAdvanced skill in Python and RAdvanced 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 CloudUnderstanding of data models, large datasets, business/technical requirements, BI tools, statistical programming languages, and librariesFamiliar with Data Engineering conceptsFamiliar with the use of standard ETL tools and techniquesFamiliar with the concepts and application of data mapping and building requirementsDemonstrates a deep understanding of multiple data-related conceptsFamiliar with Data Integration, Data Governance, and Data WarehousingAdvanced skill in Data Management, Data Validation & Cleansing, and Information AnalysisThanks and RegardsGulshan SrivasIT TECHNICAL RECRUITEREmail: [Email Address]
#J-18808-Ljbffr
Vienna, Virginia-HybridDuration:
6+ MonthsJob Description:
Provide independent data science, machine learning, and analytical insights using member, financial, and organizational data to support mission-critical decision-making for Compliance-Complaints. Understand business needs and identify opportunities for improvements to products, services, and processes to meet business objectives through the use of cutting-edge data science. Create descriptive, predictive, and prescriptive models and insights to drive impact across the organization. Regarded as an advanced professional in the data science field. Conduct complex work under minimal supervision and with wide latitude for independent judgment. Individual contributor and mentor to junior staff.Support the delivery of strategic advanced analytics solutions across the organization with solutions drawing on descriptive, predictive, and prescriptive analytics and modelingLeverage a broad set of modern technologies including Python, R, and Spark to analyze and gain insights within large data setsManage, architect, and analyze big data to build data-driven insights and high-impact data modelsEvaluate 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 eventsProvide analytics insights and solutions to solve complex business problemsApply business knowledge and advanced statistical modeling techniques when building data structures and toolsCollaborate with other team members, subject matter experts, pods, and delivery teams to deliver strategic advanced analytic-based solutions from design to deploymentExamine data from multiple sources and share insights with leadership and stakeholdersTransform data presented in models, charts, and tables into a format that is useful to the business and aids in effective decision-makingPoint of contact between the data analyst/data engineer and the project/functional analytics leadsDevelop and maintain an understanding of relevant industry standards, best practices, business processes, and technology used in modeling and within the financial services industryIdentify improvements to the way in which analytics service the entire functionRecognize potential issues and risks during the analytics project implementation and suggest mitigation strategiesPrepare project deliverables that are valued by the business and present them in such a manner that they are easily understood by project stakeholdersAssess new and existing model's overall fit/suitability with its intended use and purposeMinimum 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 experienceAbility to understand complex business problems and determine what aspects require optimization and articulate those aspects in a clear and concise mannerAdvanced skill in communicating actionable insights using data to technical and non-technical audiencesSignificant experience working in dynamic, research-oriented groups with several ongoing concurrent projectsDemonstrates advanced functional knowledge of data visualization libraries such as matplotlib or ggplot2; knowledge of other visualization tools such as Microsoft Power BI and TableauAbility to manipulate raw data within visualization tools to create effective dashboards that communicate end-to-end data outcomes visuallyAdvanced storytelling with data skillsExceptional technical writing skillsAdvanced skill in descriptive, predictive, and prescriptive analytics and modeling; demonstrated success in building models that are deployed and have made measurable business impactSignificant 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 learningAdvanced 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 lifecycleAdvanced skill data mining, data wrangling, and data transformation with both structured and unstructured data; deep understanding of data modelsAdvanced skill interpreting, extrapolating, and interpolating data for statistical research and modelingAdvanced skill in Data Interpretation, Qualitative and Quantitative AnalysisAdvanced skill in Python and RAdvanced 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 CloudUnderstanding of data models, large datasets, business/technical requirements, BI tools, statistical programming languages, and librariesFamiliar with Data Engineering conceptsFamiliar with the use of standard ETL tools and techniquesFamiliar with the concepts and application of data mapping and building requirementsDemonstrates a deep understanding of multiple data-related conceptsFamiliar with Data Integration, Data Governance, and Data WarehousingAdvanced skill in Data Management, Data Validation & Cleansing, and Information AnalysisThanks and RegardsGulshan SrivasIT TECHNICAL RECRUITEREmail: [Email Address]
#J-18808-Ljbffr