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Data Scientist (DS)* - Skill Level 4 (NGA-W)
Data Scientist:
Integrates, develops, and maintains analytic models, visualizations, and tools to deter, detect, and mitigate insider threats. Develops data analytics and visualizations involving the application of proven industry standard data science principles, practices, and techniques in the effort to identify anomalous events and potential insider threats. Maintains and develops risk scoring and other data analytics tools to support detection and data analysis implementations and/or sustainment. Captures, maintains and accumulates statistics that show quantities and timelines for products and data transferred from one domain to another domain. Support the integrity of the system through metrics collection on system errors, failures and downtime.
Duties include:
• Apply extensive knowledge to integrate, develop, and maintain analytic models, visualizations,
and tools to evaluate, analyze and communicate internal/external user behavior and overarching
enterprise or portfolio performance.
• Provide statistical and mathematical support in assisting in the analysis and interpretation of a
wide range of data to help understand and improve the customer's experience.
• Leverage a range of data sources (e.g., Web traffic, customer requests for information, survey
responses, production databases, etc.) for an understanding of what drives a positive customer
experience.
• Provide insights that will be used to inform decisions and agency operational strategies, in
partnership with teams examining website design, customer interactions, featured content, and
future products and services.
• Applies business analytics and customer segmentation techniques in any corporate function,
e.g. marketing analytics, consumer analytics, operations analysis, human capital analytics, or other
relevant fields.
• Maintain, move, and manipulate data between applications, using appropriate software/code:
Apache Spark, ElasticSearch, R, Python, Kibana and others as technology evolves.
• Establish an agile analytics process that provides better insight into ongoing analytic/data
visualization activities.
• Manage an inventory of implemented dashboards, other analytic products and current product
backlog for implementation.
Required Skills and Experience:
• Demonstrated experience developing data analytics models and visualizations employing
proven industry standards in statistic/data science principals, practices, and techniques in the
analyses of business data.
• Demonstrated experience developing dashboards to effectively convey site metrics to nontechnical audiences, to include but not limited to:
• communicating warnings and limitations of both coding techniques and statistical analyses
depicting current state and providing insight to improvement plan implementation strategies and
milestone achievement.
• Demonstrated experience working with commercial-off-the-shelf (COTS) statistical software
or tools for data visualization (i.e., SPSS, SAS, MatLab, Tableau, etc.).
• Demonstrated experience data mining, to include developing, manipulating, or maintaining
databases.
• Demonstrated experience utilizing computer programs, software, or a variety of coding languages
(i.e., Python, MySQL, D3, SPSS, SAS, Visual Basic, R, etc.) to summarize statistical data and
create documents, reports and presentations.
• Demonstrated ability to proactively identify methods and approaches to expand and enhance the
analytic capacity and ability of an existing portfolio.
Desired Skills:
• Demonstrated experience effectively communicating with various partners, stakholders, or
customers on the value of statistical and data science methods to include but not limited to:
o the strength of models/formulas,
o their limitations, warnings and weaknesses in various applications.
• Demonstrated experience embracing and participating in a culture of knowledge sharing to broaden the understanding of:
o advanced methods or
o niche statistical methods and
o data science analytic methods and
o coding techniques to include fundamental understanding of model/formula strength, limitations, warnings and weaknesses when applied in various scenarios.
Full Time
$120k-147k (estimate)
10/27/2023
04/25/2024
The job skills required for Data Scientist include Data Science, Python, Insight, Data Analysis, Futures, Data Analytics, etc. Having related job skills and expertise will give you an advantage when applying to be a Data Scientist. That makes you unique and can impact how much salary you can get paid. Below are job openings related to skills required by Data Scientist. Select any job title you are interested in and start to search job requirements.
The following is the career advancement route for Data Scientist positions, which can be used as a reference in future career path planning. As a 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 Data Scientist. You can explore the career advancement for a Data Scientist below and select your interested title to get hiring information.
If you are interested in becoming a 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 Data Scientist for your reference.
Step 1: Understand the job description and responsibilities of an Accountant.
Quotes from people on Data Scientist job description and responsibilities
Data scientists work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals.
12/22/2021: Dallas, TX
Data scientists are meant to use their technology and social science skills to develop different trends and manage data wisely.
02/17/2022: Lompoc, CA
A data scientist develops software to structure the raw data.
02/16/2022: Lansing, MI
Data scientist will need to meet with their business stakeholders early and often to ensure that they are on the same page about the goals and deliverables of the project.
02/12/2022: San Diego, CA
Data scientists may spend some of their time working on ad hoc data requests, but these types of requests should only take up a small portion of their time.
02/01/2022: Peoria, IL
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 Data Scientist jobs
Analyzing data from multiple angles and searching for trends that could reveal problems or opportunities.
01/31/2022: Passaic, NJ
Data scientists lay a solid foundation to help perform all kinds of analysis.
01/31/2022: Champaign, IL
Data scientists are also expected to have stronger software engineering skills that data analysts.
02/19/2022: Springfield, OR
Business analysts are focused on reporting, just like data analysts.
02/04/2022: Jamestown, NY
A data scientist should understand the assumptions that need to be met for each statistical test.
03/04/2022: Hialeah, FL
Step 3: View the best colleges and universities for Data Scientist.