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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?

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

Let’s say you work for a social media company that has just done a launch in a new city. Looking at weekly metrics, you see a slow decrease in the average number of comments per user from January to March in this city.

The company has been consistently growing new users in the city from January to March.

What are some reasons why the average number of comments per user would be decreasing and what metrics would you look into?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

What metric could be used to measure if active users are still engaging on the platform despite an overall decrease in the average number of comments per user?

Decreasing Comments

How would you investigate a decline in the average number of comments per user?

Theron Solutions Salaries by Position

Key Responsibilities: <ul><li>We are looking for experienced data science professional, who can handle commercial analytics projects with proficiency. Additionally, domains expertise on Sales Force analytics or Payer analytics or Patient or digital analytics or Brand Performance analytics will be a value add</li><li>Model Development: Design, develop, and implement machine learning models through EDA, feature engineering and using a variety of algorithms (e.g., regression, classification, clustering, neural networks, ensemble methods)</li><li>MLOps: Establish and maintain MLOps practices to ensure seamless deployment, monitoring, and maintenance of ML models in production environments.</li><li>Model Evaluation: Evaluate model performance using appropriate metrics and techniques, and iterate on models to improve accuracy and efficiency.</li><li>Collaboration: Work closely with data engineers and business stakeholders to integrate ML models into applications and workflows.</li><li>Documentation: Document model development processes, assumptions, and results to ensure reproducibility and transparency.</li><li>Continuous Learning: Stay updated with the latest advancements in AI/ML including LLMs, MLOps, to continuously improve skills and knowledge.</li></ul> About you: <ul><li>Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.</li><li>Experience: 4+ years of experience in data science and machine learning, with a focus on model development and MLOps.</li><li>Domain Expertise: Experience in pharma commercial analytics for at least 2+ years preferably in sales force targeting, patient journey predictions</li><li>Technical Skills: Proficiency in programming languages such as Pyspark, Python or R, and experience with ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn)</li><li>MLOps Tools: Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model deployment and monitoring.</li><li>Data Handling: Strong skills in SQL and experience in snowflake, Dataiku, Databricks is a plus</li><li>Problem-Solving: Excellent analytical and problem-solving skills, with the ability to translate business problems into data science solutions.</li><li>Communication: Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.</li></ul> Equal Opportunity Employer: Our client is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at our client are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. We will not tolerate discrimination or harassment based on any of these characteristics.

Key Responsibilities: <ul><li>We are looking for experienced data science professional, who can handle commercial analytics projects with proficiency. Additionally, domains expertise on Sales Force analytics or Payer analytics or Patient or digital analytics or Brand Performance analytics will be a value add</li><li>Model Development: Design, develop, and implement machine learning models through EDA, feature engineering and using a variety of algorithms (e.g., regression, classification, clustering, neural networks, ensemble methods)</li><li>MLOps: Establish and maintain MLOps practices to ensure seamless deployment, monitoring, and maintenance of ML models in production environments.</li><li>Model Evaluation: Evaluate model performance using appropriate metrics and techniques, and iterate on models to improve accuracy and efficiency.</li><li>Collaboration: Work closely with data engineers and business stakeholders to integrate ML models into applications and workflows.</li><li>Documentation: Document model development processes, assumptions, and results to ensure reproducibility and transparency.</li><li>Continuous Learning: Stay updated with the latest advancements in AI/ML including LLMs, MLOps, to continuously improve skills and knowledge.</li></ul> About you: <ul><li>Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.</li><li>Experience: 4+ years of experience in data science and machine learning, with a focus on model development and MLOps.</li><li>Domain Expertise: Experience in pharma commercial analytics for at least 2+ years preferably in sales force targeting, patient journey predictions</li><li>Technical Skills: Proficiency in programming languages such as Pyspark, Python or R, and experience with ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn)</li><li>MLOps Tools: Experience with MLOps tools and platforms (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model deployment and monitoring.</li><li>Data Handling: Strong skills in SQL and experience in snowflake, Dataiku, Databricks is a plus</li><li>Problem-Solving: Excellent analytical and problem-solving skills, with the ability to translate business problems into data science solutions.</li><li>Communication: Strong communication and presentation skills, with the ability to explain complex concepts to non-technical stakeholders.</li></ul> Equal Opportunity Employer: Our client is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at our client are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. We will not tolerate discrimination or harassment based on any of these characteristics.

Job Insights:<ul><li>Experienced analytics consulting professional, who can handle a breadth of medical analytics projects and Document Business Requirements liasioning with stakeholders of the medical affairs function </li><li>Maintain all the know how’s including but not limited to - Data Mapping and business rules for KPIs arising from Medical Data sources, Veeva CRM & Master Data Management (MDM) along with few ad-hoc spreadsheet-based sources as defined by stakeholders </li><li>Translate business requirements related to KOLs, MSLs, Scientific Share of Voice among others to technical specifications </li><li>Provide technical and business leadership/ mentorship to junior team members; groom them for additional responsibilities </li><li>Acquire, implement and provide knowledge transfer to Client’s stakeholders or another external stakeholder as instructed by Client’s NA on the business requirements with extensive documentation </li><li>Collaborate with other members within the team to innovate through automation / new ideas / capabilities / tools </li><li>Lead client communication, providing clients with periodic updates and insights / recommendations through appropriate channels (conference calls / emails) </li><li>Meaningfully communicate insights and information to a broad group of stakeholders through excellent oral and written communication </li><li>Assist in the creation of dashboards, reports, and visualizations that provide actionable insights to commercial teams </li><li>Work with technical teams to support data integration efforts, ensuring accurate and consistent data flow across systems, including CRM, medical analytics and MDM </li><li>Perform data validation and analysis to ensure the quality of data being used for analytics and reporting, identifying discrepancies and working to resolve them </li><li>Support the mapping of source data to target systems, ensuring proper data lineage and governance practices are followed </li></ul> About you: <ul><li> 8+ years of experience with Graduate/Post-Graduate/ MBA </li><li>Experience working with Tableau, SQL, knowledge of data sources like Veeva CRM, and medical data sources , MDM </li><li>Experience in pharmaceutical analytics & medical affairs is a must have </li><li>Experience in data visualization platforms like Tableau </li><li>Experience of working in Agile environment a plus </li><li>Ability to derive KPIs from data sets to create reports and dashboards </li><li>Strong presentation and communication skills" </li></ul> Equal Opportunity: Our client is an Equal Opportunity Employer and Prohibits Discrimination and Harassment of Any Kind: We are committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. All employment decisions at our client are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion or belief, national, social or ethnic origin, sex (including pregnancy), age, physical, mental or sensory disability, HIV Status, sexual orientation, gender identity and/or expression, marital, civil union or domestic partnership status, past or present military service, family medical history or genetic information, family or parental status, or any other status protected by the laws or regulations in the locations where we operate. We will not tolerate discrimination or harassment based on any of these characteristics

Theron Solutions Interview Questions

Theron Solutions Interview Guides

Theron Solutions Interview Questions

Theron Solutions Salaries by Position

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