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What is a Meta Data Science job?

A Meta Data Science job involves using data analysis, machine learning, and statistical techniques to drive insights and decision-making at Meta. Data scientists in this role work with large-scale datasets to optimize products, improve user experiences, and develop predictive models. They collaborate with engineers, product managers, and researchers to solve complex business problems. The role requires expertise in programming, data visualization, and experimental design to extract meaningful information from data.

What are the key skills and qualifications needed to thrive in the Meta Data Science position, and why are they important?

To excel in Meta Data Science, a strong background in statistics, machine learning, and data analysis, often supported by an advanced degree in a quantitative field, is essential. Proficiency in programming languages like Python or R, experience with big data platforms (such as Hadoop or Spark), and knowledge of data visualization tools are typically required, as well as relevant certifications like those from Google, AWS, or Microsoft. Exceptional problem-solving, communication, and teamwork skills set top candidates apart in this collaborative and data-driven environment. These competencies enable professionals to generate actionable insights, build scalable models, and effectively communicate findings to both technical and non-technical stakeholders.

What are typical daily responsibilities for someone in a Meta Data Science role?

In a Meta Data Science role, your daily tasks often involve analyzing large datasets to extract insights, developing and validating predictive models, and communicating findings to diverse teams. You will work closely with product managers, engineers, and other data professionals to design experiments and optimize business strategies. The role frequently requires presenting complex analyses in approachable terms and iterating on data solutions in response to feedback. You may also contribute to the development of internal data tools or pipelines, ensuring data quality and accessibility across the organization.
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What are the most commonly searched types of Meta Data Science jobs in Indiana? The most popular types of Meta Data Science jobs in Indiana are:
What are popular job titles related to Meta Data Science jobs in Indiana? For Meta Data Science jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Meta Data Science jobs in Indiana look for? The top searched job categories for Meta Data Science jobs in Indiana are:
Meta Data Science jobs near you
Infographic showing various Meta Data Science job openings in Indiana as of May 2026, with employment types broken down into 1% Internship, 98% Full Time, and 1% Temporary. Highlights an 95% Physical, and 5% Remote job distribution.
Data Quality Lead

Data Quality Lead

Yochana IT Solutions Inc

Indianapolis, IN

Full-time

Posted 16 days ago

Job description

Company Description

Reach me at chaitu AT yochanait DOT com for more information 

Job Description

Job Title: Data Quality Lead

Job Location: Columbus IN

Project Duration: 6 months

GC/ USC/ H1B

Mandatory Skills

Minimum of 4 years' hands-on expertise with the data modeling and data management

1-year experience with Microsoft Data Quality Services

Exposure to Hadoop (Hortonworks preferable) stack (e.g. HDFS, MapReduce, Spark, Pig, Hive, Hbase, Flume etc.)

Minimum of 5 years of experience in database development and SQL

Minimum 2 years with Tableau

Minimum 2 years with R, Python, or Spark

Desired Skills

Technical understanding of Data Science

Hadoop and Analytics experience (MapReduce/R)

Job Description:

Implementation of Data Quality solutions consisting of meta data management, data quality, data validation, and data governance solutions

Deliver solutions via the Agile development method

Working with architects and providing implementation details to team members

Production of quality deliverables in a timely manner

Sharing knowledge and experience with various groups within an organization

Responsibilities:

Ability to communicate clearly with customers

Ability to independently analyze, diagnose, troubleshoot, and drive issues to resolution with minimal supervision

Ability to work independently within a large team environment

Ability to articulate and share knowledge as it pertains to data governance applications and architecture

Experience working in a team setting and brainstorming design for applications

Ability to quickly learn and show competence in new Advanced Analytics and Big Data technologies

Consulting experience is a plus

Additional Information

All your information will be kept confidential according to EEO guidelines.

Apply