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SENECA RESOURCES
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Senior Data Scientist
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$115k-141k (estimate)
Full Time Just Posted
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SENECA RESOURCES is Hiring a Senior Data Scientist Near Vienna, VA

One of our top clients is hiring a Senior Data Scientist:

Business Unit: Compliance & Public Policy

Location: HDQ, Vienna VA / Hybrid

* We will only accept the following: US Citizens, Green Card Holders, TN Visa, Green Card EAD's.

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

• 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

Desired Qualifications and Education Requirements:

• 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

About Seneca Resources:

Seneca Resources is a client driven provider of strategic Information Technology consulting services and Workforce Solutions to government and industry. Seneca Resources is a leading IT services provider with offices in Virginia, Alabama, Georgia, Florida and Texas that service clients throughout the United States.

We are an Equal Opportunity Employer and value the benefits of diversity in our workplace.

Job Summary

JOB TYPE

Full Time

SALARY

$115k-141k (estimate)

POST DATE

07/06/2024

EXPIRATION DATE

07/19/2024

WEBSITE

senecahq.com

HEADQUARTERS

RESTON, VA

SIZE

200 - 500

FOUNDED

2010

CEO

JOSEPH WIRE

REVENUE

$10M - $50M

INDUSTRY

Wholesale

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About SENECA RESOURCES

Seneca Resources is an Information Technology and Engineering professional services firm supporting clients in the public and private sectors. For over 15 years, Seneca Resources has successfully delivered services and solutions to organizations ranging from small businesses to Fortune 100 companies and numerous branches of the Federal Government. Areas of technical and functional expertise include: CIO and CTO Services / CISO Services / ERP Solutions / Managed Security Services / CRM Solutions / Data Analytics / Utility SMART Solutions / Cloud Implementation and Migration / Project Management... Office (PMO) and Project Management (PMP) / Microsoft Solutions Seneca Resources supports clients globally with industry expertise in the following verticals: Energy / Utilities / Banking / Automotive / Manufacturing / Healthcare / Defense / National Security / Retail / Digital Media / Oil & Gas / eCommerce More
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The following is the career advancement route for Senior Data Scientist positions, which can be used as a reference in future career path planning. As a Senior Data Scientist, it can be promoted into senior positions as a Data Scientist IV that are expected to handle more key tasks, people in this role will get a higher salary paid than an ordinary Senior Data Scientist. You can explore the career advancement for a Senior Data Scientist below and select your interested title to get hiring information.

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If you are interested in becoming a Senior Data Scientist, you need to understand the job requirements and the detailed related responsibilities. Of course, a good educational background and an applicable major will also help in job hunting. Below are some tips on how to become a Senior Data Scientist for your reference.

Step 1: Understand the job description and responsibilities of an Accountant.

Quotes from people on Senior Data Scientist job description and responsibilities

Senior Data Scientists rae responsible in formulating, suggesting, and managing data-driven projects which are geared at furthering the business's interests.

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Collating and cleaning data from various entities for later use by junior data scientists.

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Delegating tasks to Junior Data Scientists in order to realize the successful completion of projects.

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They also monitor the performance of Junior Data Scientists and providing them with practical guidance, as needed.

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May also be tasked in selecting and employing advanced statistical procedures to obtain actionable insights.

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Step 2: Knowing the best tips for becoming an Accountant can help you explore the needs of the position and prepare for the job-related knowledge well ahead of time.

Career tips from people on Senior Data Scientist jobs

Present final result to stakeholders. Make adjustments based on feedback.

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Learn the required skills to become a data scientist.

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Review additional data scientist certifications and post-graduate learning.

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Ask the right questions to begin the discovery process.

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Choose one or more potential models and algorithms.

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Step 3: View the best colleges and universities for Senior Data Scientist.

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