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Suppose there exists a new airline named Jetco that flies domestically across North America. Jetco recently had a study commissioned that tested the boarding time of every airline, and it came out that Jetco had the fastest average boarding times of any airline.

What factors could have biased this result, and what would you look into?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

What could potentially bias the average boarding time in favor of an airline that only flies domestically?

Boarding Times Bias

A new airline came out as the fastest average boarding times compared to other airlines.  What factors could have biased this result and what would you look into?

Let’s say we have a table with an <code>id</code> and <code>name</code> fields. The table holds over 100 million rows and we want to sample a random row in the table without throttling the database.

Write a query to randomly sample a row from this table.

Input:

<code>big_table</code> table

<table>
<thead>
<tr>
<th>Columns</th>
<th>Type</th>
</tr>
</thead>

<tbody>
<tr>
<td><code>id</code></td>
<td>INTEGER</td>
</tr>

<tr>
<td><code>name</code></td>
<td>VARCHAR</td>
</tr>
</tbody>
</table>

Write a query to randomly sample a row from a big table.

Random SQL Sample

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

What is a key disadvantage of the F-test when compared to multiple t-tests?

What is a key disadvantage of the F-test when compared to multiple t-tests?

Hundreds of Hypotheses

You are testing hundreds of hypotheses with many t-tests. What considerations should be made?

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<h3>Job Description</h3><div>Job Description<div>Data Engineer Machine Learning My name is Bill Stevens, and I have a new six month plus Data Engineer Machine Learning opportunity available for a major firm located in Bethlehem, Pennsylvania that could be of interest to you, please review my specification below. The work schedule will be a hybrid, two days a week in the firms Bethlehem, Pennsylvania office and three days remote. This position pays $90.00 per hour on a w-2 hourly basis or $100.00 per hour on a Corp basis. The Corp rate is for independent contractors only and not third-party firms. No Visa entanglements and no H1-B holding companies. The ideal candidate will: Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions. Support data discovery & data preparation for model development. Perform detailed analysis of raw data sources by applying business context and collaborate with cross-functional teams to transform raw data into curated & certified data assets to be used for ML and BI use cases. Collaborate with data science and data engineering team to build scalable and reproducible machine learning pipelines for training and inference. Implement machine learning models into operations and processes via batch, streaming and API methods. Monitor and troubleshoot data pipeline performance, identifying and resolving bottlenecks and issues. Develop, test, and maintain robust tools, frameworks, and libraries that standardize and streamline the data & machine learning lifecycle. Contribute to developing and maintaining end-to-end MLOps lifecycle to automate machine learning solutions development and delivery. Implement robust monitoring framework for model performance. Collaborate with cross-functional teams of Data Science, Data Engineering, business units and various IT teams. Create and maintain effective documentation for project and practices ensuring transparency and effective team communication. Requirements: Bachelor’s or master’s degree with 5+ years of experience in Computer Science, Data Science, Engineering, or a related field. 4+ years of experience in working with Python, SQL, PySpark and bash scripts. Proficient in software development lifecycle and software engineering practices. 2+ years of hands-on experience in using Databricks platform 3+ years of hands-on experience in operationalizing Machine Learning solutions which are used in live production processes. 2+ years of experience and proficiency in API development using FastAPI frameworks and familiarity with containerization technologies such as docker or Kubernetes. 3+ years of experience in developing and maintaining robust data pipelines data to be used by Data Scientists to build ML Models. 3+ years of experience working with Cloud Data Warehousing (Redshift, Snowflake, Databricks SQL or equivalent) platforms and experience in working with distributed framework like Spark. Solid understanding of machine learning life cycle, data mining, and ETL techniques. Experience with machine learning frameworks such as Keras or PyTorch and libraries such as scikit-learn, xgboost). Hands-on experience in building and maintaining tools and libraries which have been used by multiple teams across organization. Proficient in understanding and incorporating software engineering principles in design & development process. Hands on experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Github, Bitbucket), Orchestration (Airflow, Prefect or equivalent) Excellent communication skills and ability to work and collaborate with cross functional teams across technology and business. Pluses only: Familiarity with deep learning frameworks and deploying deep learning models for production use cases. Familiarity in using GPU compute either for model training or inference. Understanding of Large language models (LLM) and MLOps lifecycle for operationalizing LLM models. The interview process will include an initial telephone or Zoom screening. Please let me know your interest for this position, availability to interview and start for this position along with a copy of your recent resume.</div></div>

<h3>Job Description</h3><div>Job Description<div>Data Engineer Machine Learning My name is Bill Stevens, and I have a new six month plus Data Engineer Machine Learning opportunity available for a major firm located in Bethlehem, Pennsylvania that could be of interest to you, please review my specification below. The work schedule will be a hybrid, two days a week in the firms Bethlehem, Pennsylvania office and three days remote. This position pays $90.00 per hour on a w-2 hourly basis or $100.00 per hour on a Corp basis. The Corp rate is for independent contractors only and not third-party firms. No Visa entanglements and no H1-B holding companies. The ideal candidate will: Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions. Support data discovery & data preparation for model development. Perform detailed analysis of raw data sources by applying business context and collaborate with cross-functional teams to transform raw data into curated & certified data assets to be used for ML and BI use cases. Collaborate with data science and data engineering team to build scalable and reproducible machine learning pipelines for training and inference. Implement machine learning models into operations and processes via batch, streaming and API methods. Monitor and troubleshoot data pipeline performance, identifying and resolving bottlenecks and issues. Develop, test, and maintain robust tools, frameworks, and libraries that standardize and streamline the data & machine learning lifecycle. Contribute to developing and maintaining end-to-end MLOps lifecycle to automate machine learning solutions development and delivery. Implement robust monitoring framework for model performance. Collaborate with cross-functional teams of Data Science, Data Engineering, business units and various IT teams. Create and maintain effective documentation for project and practices ensuring transparency and effective team communication. Requirements: Bachelor’s or master’s degree with 5+ years of experience in Computer Science, Data Science, Engineering, or a related field. 4+ years of experience in working with Python, SQL, PySpark and bash scripts. Proficient in software development lifecycle and software engineering practices. 2+ years of hands-on experience in using Databricks platform 3+ years of hands-on experience in operationalizing Machine Learning solutions which are used in live production processes. 2+ years of experience and proficiency in API development using FastAPI frameworks and familiarity with containerization technologies such as docker or Kubernetes. 3+ years of experience in developing and maintaining robust data pipelines data to be used by Data Scientists to build ML Models. 3+ years of experience working with Cloud Data Warehousing (Redshift, Snowflake, Databricks SQL or equivalent) platforms and experience in working with distributed framework like Spark. Solid understanding of machine learning life cycle, data mining, and ETL techniques. Experience with machine learning frameworks such as Keras or PyTorch and libraries such as scikit-learn, xgboost). Hands-on experience in building and maintaining tools and libraries which have been used by multiple teams across organization. Proficient in understanding and incorporating software engineering principles in design & development process. Hands on experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Github, Bitbucket), Orchestration (Airflow, Prefect or equivalent) Excellent communication skills and ability to work and collaborate with cross functional teams across technology and business. Pluses only: Familiarity with deep learning frameworks and deploying deep learning models for production use cases. Familiarity in using GPU compute either for model training or inference. Understanding of Large language models (LLM) and MLOps lifecycle for operationalizing LLM models. The interview process will include an initial telephone or Zoom screening. Please let me know your interest for this position, availability to interview and start for this position along with a copy of your recent resume.</div></div>

Senior C++ Software EngineerFull TimeColumbia, MDHybrid (3 days onsite) Our client is seeking a highly skilled and experienced Senior C++ Software Engineer to join our innovative team of dedicated, diverse professionals. The ideal candidate possesses a deep understanding of C and C++, a proven ability to navigate complex codebases, and a passion for crafting robust, efficient, and user-friendly software solutions. Requirements<ul><li>Analyze, design, and develop high-performance C++ applications with sophisticated graphical user interfaces.</li><li>Collaborate with cross-functional teams to understand project requirements, translating them into intuitive and visually appealing user experiences.</li><li>Develop and maintain efficient build systems and tools.</li><li>Optimize code for performance, scalability, and visual responsiveness.</li><li>Conduct code reviews and provide constructive feedback to team members.</li><li>Identify opportunities for code refactoring and improvement.</li><li>Stay up-to-date with the latest C++ standards, GUI development best practices, and emerging technologies.</li></ul> Qualifications<ul><li>Strong proficiency in C and C++, including low-level system programming and optimization techniques.</li><li>Extensive experience in GUI development using relevant frameworks and toolkits.</li><li>Solid understanding of UI/UX design principles and user-centered development methodologies.</li><li>Extensive experience with build systems (e.g., Make, CMake).</li><li>Solid understanding of multithreading and concurrent programming.</li><li>Expertise in version control systems (e.g., Git).</li><li>Proven ability to analyze and understand complex codebases.</li><li>Excellent problem-solving and debugging skills.</li><li>Strong communication and collaboration abilities.</li><li>Ability to obtain a Top Secret security clearance</li></ul> Preferred Qualifications<ul><li>Experience with DSP algorithms and implementation.</li><li>Background in high-performance computing (HPC).</li><li>Strong algorithmic and data structures knowledge.</li><li>Experience with refactoring and code optimization.</li><li>Proficiency in automated testing frameworks.</li><li>Experience with user interface development.</li><li>Embedded systems development experience.</li><li>GPU programming experience.</li><li>Experience with python / rust / c#.</li></ul>

<h3>Job Description</h3><div>Job Description<div>Data Engineer Machine Learning My name is Bill Stevens and I have a new six month plus Data Engineer Machine Learning opportunity available for a major firm located in Bethlehem, Pennsylvania that could be of interest to you, please review my specification below. The work schedule will be a hybrid, two days a week in the firms Bethlehem, Pennsylvania office and three days remote. This position pays $90.00 per hour on a w-2 hourly basis or $100.00 per hour on a Corp basis. The Corp rate is for independent contractors only and not third-party firms. No Visa entanglements and no H1-B holding companies. The ideal candidate will: Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions. Support data discovery & data preparation for model development. Perform detailed analysis of raw data sources by applying business context and collaborate with cross-functional teams to transform raw data into curated & certified data assets to be used for ML and BI use cases. Collaborate with data science and data engineering team to build scalable and reproducible machine learning pipelines for training and inference. Implement machine learning models into operations and processes via batch, streaming and API methods. Monitor and troubleshoot data pipeline performance, identifying and resolving bottlenecks and issues. Develop, test, and maintain robust tools, frameworks, and libraries that standardize and streamline the data & machine learning lifecycle. Contribute to developing and maintaining end-to-end MLOps lifecycle to automate machine learning solutions development and delivery. Implement robust monitoring framework for model performance. Collaborate with cross-functional teams of Data Science, Data Engineering, business units and various IT teams. Create and maintain effective documentation for project and practices ensuring transparency and effective team communication. Requirements: Bachelor’s or master’s degree with 5+ years of experience in Computer Science, Data Science, Engineering, or a related field. 4+ years of experience in working with Python, SQL, PySpark and bash scripts. Proficient in software development lifecycle and software engineering practices. 2+ years of hands-on experience in using Databricks platform 3+ years of hands-on experience in operationalizing Machine Learning solutions which are used in live production processes. 2+ years of experience and proficiency in API development using FastAPI frameworks and familiarity with containerization technologies such as docker or Kubernetes. 3+ years of experience in developing and maintaining robust data pipelines data to be used by Data Scientists to build ML Models. 3+ years of experience working with Cloud Data Warehousing (Redshift, Snowflake, Databricks SQL or equivalent) platforms and experience in working with distributed framework like Spark. Solid understanding of machine learning life cycle, data mining, and ETL techniques. Experience with machine learning frameworks such as Keras or PyTorch and libraries such as scikit-learn, xgboost). Hands-on experience in building and maintaining tools and libraries which have been used by multiple teams across organization. Proficient in understanding and incorporating software engineering principles in design & development process. Hands on experience with CI/CD tools (e.g., Jenkins or equivalent), version control (Github, Bitbucket), Orchestration (Airflow, Prefect or equivalent) Excellent communication skills and ability to work and collaborate with cross functional teams across technology and business. Pluses only: Familiarity with deep learning frameworks and deploying deep learning models for production use cases. Familiarity in using GPU compute either for model training or inference. Understanding of Large language models (LLM) and MLOps lifecycle for operationalizing LLM models. The interview process will include an initial telephone or Zoom screening. Please let me know your interest for this position, availability to interview and start for this position along with a copy of your recent resume.</div></div>

Pri Technology Interview Questions

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Pri Technology Interview Questions

Pri Technology Salaries by Position

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