Dice
Senior Data Scientist
Dice, Vienna, Virginia, United States, 22184
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Allwyn Corporation, is seeking the following. Apply via Dice today!
Position: Data ScientistLocation: Hybrid in Vienna, VADuration: Long TermJob 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.
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.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.
Qualifications and Education Requirements:
All Data Scientist RolesMaster'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 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.
Desired Qualifications:
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.
Desired Qualifications and Education Requirements:
All Data Scientist RolesDoctoral degree in Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field.Familiar with project management concepts and frameworks such as Agile Frameworks (SAFE), Communication Strategy and Management, Delivery Excellence and Requirements management.
Senior Data Scientist#J-18808-Ljbffr
Position: Data ScientistLocation: Hybrid in Vienna, VADuration: Long TermJob 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.
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.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.
Qualifications and Education Requirements:
All Data Scientist RolesMaster'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 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.
Desired Qualifications:
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.
Desired Qualifications and Education Requirements:
All Data Scientist RolesDoctoral degree in Statistics, Mathematics, Computer Science, Engineering or another quantitative field, or related field.Familiar with project management concepts and frameworks such as Agile Frameworks (SAFE), Communication Strategy and Management, Delivery Excellence and Requirements management.
Senior Data Scientist#J-18808-Ljbffr