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Some of the examples of work but not limited to, in this role are:
Data Quality Assessment - At intake, the Data Scientist shall assess the quality of the data. Data quality assessment is a continual process and should include qualitative and quantitative assessment to include but not limited to summarizing all variables and providing statistics such as minimum, maximum, mean, median and number of missing values. Prior to providing preliminary and final results, the Data Scientist is responsible for conducting a data quality assessment to resolve all errors and data inconsistencies.
Data Cleaning - The process of transforming, parsing, aggregation and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of this process is to ensure the quality and usefulness of data. The process goal is for analysts typically spend the majority of their time in the process of data wrangling compared to the actual analysis of the data.
Data File Review and Cleaning Results - The Contractor shall document its understanding of each file review and cleaning task in its project management plan. During the file review the Contractor shall scrutinize the accuracy of large loan file submissions from respondents and summarize observations in a memo. This summary should include, but is not limited to, missing values, logically inconsistent values, or implausible values by comparing it to other sources of information, such as underlying loan documents. Subsequently, the Contractor shall clean data by handling missing values, logically inconsistent values, implausible values and as well as recode, create, or impute any variables needed. When required, the Contactor shall merge multiple databases, for example, combining a respondents administrative data with U.S. Census or Home Mortgage Disclosure Act (HMDA) data. The contractor shall provide a detailed data file that allows the government to review and replicate steps taken to analyze and clean datasets. Examples of steps taken include inputting data, merging datasets, creating variables, and conducting analysis. The contractor shall have the capability to perform data analysis to achieve the performance objectives in the PWS utilizing the following software:
Data Analysis Reports Review:
Requirements:
Experience working with Housing and Urban Development is preferred.
3 years professional experience in the field.
Should be proficient in using SAS and R or STATA software for statistical and regression analysis.
Job Type: Full-time
Pay: $113,000.00 - $143,000.00 per year
Benefits:
Experience level:
Schedule:
Ability to Relocate:
Work Location: In person
Full Time
IT Outsourcing & Consulting
$120k-148k (estimate)
02/11/2024
05/08/2024
technuf.com
ROCKVILLE, MD
50 - 100
2011
Private
FAISAL QUADER
$10M - $50M
IT Outsourcing & Consulting
The job skills required for Data Scientist include Analysis, Data Analysis, Economics, SAS, Project Management, 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.