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Entry Level Amazon Data Science Jobs in Pittsburgh, PA

Deloitte

Cyber - SecOps - Consultant

Pittsburgh, PA · On-site

... data science workflows * 2+ years of experience using cloud-based cybersecurity platforms such as Google SecOps, Amazon Web Services (AWS), or Microsoft Azure * 1+ years of experience with security ...

Pwc

Data Engineer - Senior Associate

Pittsburgh, PA · On-site

$77K - $202K/yr

... Amazon Web Services (AWS) and Azure Data Factory to enhance data engineering capabilities ... Management Information Systems, Computer and Information Science, Systems Engineering, Electrical ...

Thinkbrg

Fall 2027 Advisory Associate

Pittsburgh, PA · On-site

We Do Consulting Differently The Associate position is a full-time entry level consulting staff ... Bachelor's or Master's degree in economics, mathematics, data science, statistics, finance ...

Pwc

US Tech - FTO Senior Associate

Pittsburgh, PA · On-site

$55K - $187K/yr

Analytics/Data Science, Artificial Intelligence/Robotics, Business Administration/Management ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

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Entry Level Amazon Data Science information

What is the difference between Entry Level Amazon Data Science vs Entry Level Amazon Data Engineering?

AspectEntry Level Amazon Data ScienceEntry Level Amazon Data Engineering
Required CredentialsBachelor's in Data Science, Statistics, or related field; Python, R skillsBachelor's in Computer Science, Software Engineering, or related; SQL, Python, Spark skills
Work EnvironmentAnalyzing data, building models, predictive analyticsBuilding data pipelines, managing data infrastructure
Employer & Industry UsageUsed across Amazon for insights, recommendations, customer behaviorSupports data infrastructure, ETL processes, data storage

Entry Level Amazon Data Science focuses on analyzing data and creating models to inform business decisions, while Entry Level Amazon Data Engineering involves building and maintaining data pipelines and infrastructure. Both roles require technical skills but differ in their core responsibilities and daily tasks.

What are some common challenges faced by entry-level data scientists at Amazon, and how can they be addressed?

Entry-level data scientists at Amazon often encounter challenges such as working with large-scale, complex datasets and adapting to the fast-paced, results-driven environment. Navigating Amazon's proprietary tools and understanding the business context behind data projects can also be daunting at first. To overcome these challenges, new hires are encouraged to actively seek guidance from mentors, participate in team knowledge-sharing sessions, and invest time in learning Amazon's data infrastructure and workflows. Collaboration with cross-functional teams is frequent, so developing strong communication skills and a willingness to ask questions can significantly ease the transition and lead to early success.

What are the key skills and qualifications needed to thrive as an entry level Amazon data scientist, and why are they important?

To thrive as an Entry Level Data Scientist at Amazon, you typically need a strong foundation in statistics, data analysis, and programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with tools and languages such as Python, SQL, AWS, and machine learning libraries, along with experience using data visualization platforms, is highly valued. Strong problem-solving abilities, communication skills, and the ability to collaborate across teams set top candidates apart. These skills are essential to extract actionable insights from large datasets, drive data-driven decisions, and contribute effectively to Amazon’s innovative environment.

What is an entry level Amazon data science job?

An entry level Amazon data science job typically involves analyzing large datasets, building data models, and generating insights to help Amazon improve its products and services. Employees in these roles often work with teams of data scientists, engineers, and business stakeholders to solve real-world business problems. Key responsibilities may include cleaning and organizing data, using statistical and machine learning techniques, and creating visualizations to communicate findings. Entry-level positions usually require a background in statistics, computer science, or a related field, along with proficiency in programming languages like Python or R.
What are the most commonly searched types of Amazon Data Science jobs in Pittsburgh, PA? The most popular types of Amazon Data Science jobs in Pittsburgh, PA are:
What are popular job titles related to Entry Level Amazon Data Science jobs in Pittsburgh, PA? For Entry Level Amazon Data Science jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Entry Level Amazon Data Science jobs in Pittsburgh, PA look for? The top searched job categories for Entry Level Amazon Data Science jobs in Pittsburgh, PA are:
Entry Level Amazon Data Science jobs near you
Infographic showing various Entry Level Amazon Data Science job openings in Pittsburgh, PA as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Machine Learning Operations Engineer - Pittsburgh, PA, Strongsville, OH, or Dallas, TX - Full Time

Lorven Technologies

Pittsburgh, PA • On-site

Full-time

Re-posted 10 hours ago

Job description

Our client seeks an Machine Learning Operations Engineer for a Full Time project in Pittsburgh, PA, Strongsville, OH, or Dallas, TX. Below is the detailed requirement
Job Title: Machine Learning Operations Engineer
Work location : Pittsburgh, PA, Strongsville, OH, or Dallas, TX
Duration: Full Time
Summary:
Position Description
We are seeking an experienced MLOps Engineer with strong expertise in Python and big data technologies to join our team. This role focuses on operational excellence, including optimizing feature engineering pipelines and maintaining machine learning models in production environments. Desired candidate will work closely with platform and data science teams to ensure scalable, reliable, and high-performance ML workflows using existing frameworks.
Required qualifications to be successful in this role
  • Bachelor's degree preferably in Computer Science, Information technology, Computer Engineering, or related IT discipline or equivalent experience with 12+ Minimum Experience.
  • Amazon Web Services Cloud, Apache Hadoop YARN,Apache Kafka, AWS SageMaker,Big Data, Analytics & Operations,Hadoop Hive,Machine Learning,Pandas,Python
  • 6+ years of experience in software engineering, data engineering, or MLOps roles.
  • Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow.
  • Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
  • Experience with CI/CD pipelines and best practices in ML environments.
  • Hands-on experience with monitoring tools for ML pipeline health and performance.
  • Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering).
  • Experience contributing to or building internal MLOps frameworks/platforms.
  • Familiarity with SLURM clusters or other distributed job schedulers.
  • Exposure to Kafka, Spark Streaming, or other real-time data processing technologies.
  • Understanding of ML lifecycle management, including versioning, deployment, and drift detection.
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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