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60 Dataannotation Data Software Engineer Jobs Hiring in PA

DataAnnotation

Decision Scientist

Indiana, PA · On-site +1

$40/hr

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Bioinformatician - AI Trainer

Indiana, PA · On-site +1

$60/hr

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Econometrician - AI Trainer

Indiana, PA · On-site +1

$40/hr

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Geophysicist - AI Trainer

Indiana, PA · On-site +1

$60/hr

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Growth Analyst - AI Trainer

Indiana, PA · On-site +1

$60/hr

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Epidemiologist - AI Trainer

Indiana, PA · On-site +1

$60/hr

Join the DataAnnotation team and contribute to developing cutting‐edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Logistics Analyst - AI Trainer

Indiana, PA · On-site +1

$40/hr

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

DataAnnotation

Psychometrician - AI Trainer

Indiana, PA · On-site +1

$40/hr

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying ... Whether your background is in data science, astrophysics, economics, biostatistics, operations ...

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DataAnnotation Jobs Information

What are the key skills and qualifications needed to thrive as a Data Software Engineer, and why are they important?

To thrive as a Data Software Engineer, you need strong programming skills (often in Python, Java, or Scala), a solid understanding of data structures and algorithms, and a background in computer science or a related field. Familiarity with big data frameworks (like Hadoop or Spark), database systems (SQL/NoSQL), and data pipeline tools is typically required, along with relevant certifications such as AWS Certified Data Analytics. Excellent problem-solving abilities, collaboration, and effective communication are soft skills that set top performers apart. These skills ensure the efficient design, development, and optimization of robust data systems critical for driving business insights and decision-making.

What are some common challenges Data Software Engineers face when working with large datasets?

Data Software Engineers often encounter challenges related to scalability, data quality, and system performance when handling large datasets. Ensuring that data pipelines can efficiently process high volumes of data without bottlenecks requires robust architecture and frequent optimization. Additionally, maintaining data integrity and consistency across distributed systems can be complex, especially when integrating data from multiple sources. Collaboration with data scientists, analysts, and DevOps teams is key to overcoming these challenges and building reliable, efficient data solutions.

What are Data Software Engineers?

Data Software Engineers are professionals who design, build, and maintain the software systems that enable organizations to collect, process, and analyze large volumes of data. They bridge the gap between data engineering and software development by creating scalable, efficient pipelines and applications that support data-driven decision making. Their responsibilities often include developing data processing frameworks, ensuring data quality, and collaborating with data scientists and analysts to deliver actionable insights.

What is the difference between Data Software Engineer vs Data Engineer?

AspectData Software EngineerData Engineer
Primary FocusDeveloping software tools and applications for data processing and analysisBuilding and maintaining data pipelines and infrastructure
Skills & CertificationsProgramming, software development, data modeling, often with certifications in software engineeringDatabase systems, ETL tools, cloud platforms, often with certifications in data engineering
Work EnvironmentSoftware development teams, data science teams, often in tech companiesData infrastructure teams, IT departments, cloud service providers

While both roles work with data, Data Software Engineers focus on creating software solutions for data analysis, whereas Data Engineers build the infrastructure to collect, store, and process data efficiently. Both roles require programming skills and often overlap, but their core responsibilities differ in scope and focus.

What are the most popular jobs at Dataannotation in Pennsylvania?
What are the most popular states for Dataannotation Data Software Engineer Jobs?
Infographic showing various Data Software Engineer job openings at Dataannotation in Pennsylvania as of May 2026, with employment types broken down into 100% Part Time. Highlights an 100% Remote job distribution.
Simulation Engineer - AI Trainer

Simulation Engineer - AI Trainer

DataAnnotation

Indiana, PA • On-site, Remote

$40/hr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Join the DataAnnotation team and contribute to developing cutting-edge AI systems, while enjoying the flexibility of remote work and setting your own schedule. We are looking for experienced quantitative professionals to help advance AI development. AI models are increasingly capable of performing complex analytical and scientific reasoning — but these systems still need practitioners with real-world quantitative experience to validate whether the outputs actually hold up in practice.

That's where you come in. As a member of DataAnnotation's team, you'll work closely with state-of-the-art AI models on tasks like evaluating AI-generated quantitative analysis, solving technical problems, and providing feedback that directly shapes how these systems reason about data, models, and scientific problems. Whether your background is in data science, astrophysics, economics, biostatistics, operations research, or any other quantitative field, if you think rigorously about data and models, your skills are directly applicable here.

Some team members fit this work alongside a full-time role, while others treat it as their primary focus. To get started, once you sign up for an account, you'll take a short assessment (this serves as our version of an interview). If you pass, you'll receive an email confirmation, and paid work will become available on our platform.

Benefits Fully remote: work from anywhere in the US, Canada, UK, Ireland, Australia, and New Zealand. Flexible schedule: choose which projects you take on and when you work. Competitive pay: projects are paid hourly, starting at $40+ USD per hour.

Impact: help shape the future of AI systems built to reason about data and analytics. Responsibilities Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity. Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code. Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning. Qualifications 2+ years of hands‐on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end. Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time‐series forecasting). Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus. Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise). Note: Payment is made via PayPal.

We will never ask for any money from you. This job is only available to those in the US, Canada, UK, Ireland, Australia, and New Zealand. #datascience #J-18808-Ljbffr

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