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Senior Data Scientist

1 month ago

Vienna, United States Dice Full time

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 Scientist

Location: Hybrid in Vienna, VA

Duration: Long Term

Job Description:

Advanced Analytics Focused

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:

Advanced Analytics Focused

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 Roles

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

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 Roles

Doctoral 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

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