... Python, SQL, and cloud-based tools with experience in developing machine learning models and ... Preferred : • Advanced degrees (Master's, PhD) in the same fields strongly preferred, with ...
... Python, SQL, and cloud-based tools with experience in developing machine learning models and ... Preferred : • Advanced degrees (Master's, PhD) in the same fields strongly preferred, with ...
Phd Python information
What Python jobs are in-demand?
Python developers are in high demand across industries such as technology, finance, healthcare, and data science. Common roles include data scientist, machine learning engineer, backend developer, and automation engineer, often requiring knowledge of frameworks like Django or Flask and proficiency in data analysis tools. These positions typically value strong programming skills, problem-solving ability, and experience with cloud platforms and version control systems.
Can we do PhD in Python?
A PhD in Python typically refers to research involving Python programming language, often in fields like computer science, data science, or artificial intelligence. While there is no formal PhD in Python itself, students pursue doctoral degrees in related areas and use Python as a primary tool for research and development. Earning a PhD requires completing original research, coursework, and a dissertation in a relevant field, with proficiency in Python being a valuable skill for data analysis, machine learning, and software development.
What are the key skills and qualifications needed to thrive as a PhD-level Python Developer, and why are they important?
To thrive as a PhD-level Python Developer, you need advanced programming skills in Python, a relevant doctoral degree (typically in computer science, data science, or a related field), and a strong foundation in research methodologies. Experience with scientific computing libraries (such as NumPy, pandas, and SciPy), machine learning frameworks, and version control systems like Git is highly valued. Exceptional problem-solving abilities, clear communication, and the capacity to work independently are crucial soft skills for this role. These skills and qualities are essential for driving innovative research, developing robust code, and effectively collaborating within interdisciplinary teams.
What types of collaborative projects might a PhD with Python expertise typically engage in within a research or industry setting?
PhDs with strong Python skills often work on multidisciplinary projects that require data analysis, machine learning, or automation. They may collaborate with domain experts, data scientists, and software engineers to design experiments, develop analytical tools, or build scalable research prototypes. Collaborative work frequently involves contributing to codebases, sharing insights through data visualization, and participating in regular meetings to align project goals. Such environments foster both technical growth and exposure to diverse fields, supporting career advancement through impactful contributions.
Is Python in high demand?
Python is in high demand across many industries, especially for roles involving data analysis, machine learning, web development, and automation. Python developers with skills in frameworks like Django or Flask and experience with libraries such as Pandas or TensorFlow are highly sought after in the job market.
What is the highest paying job in Python?
The highest paying jobs involving Python typically include roles such as Machine Learning Engineer, Data Scientist, and Quantitative Analyst, often requiring advanced skills in algorithms, statistics, and frameworks like TensorFlow or PyTorch. These positions can offer salaries exceeding $150,000 annually, especially with experience, certifications, and work in finance, tech, or research environments.
What is a PhD Python developer?
A PhD Python developer is a professional who has earned a Doctor of Philosophy (PhD) degree and specializes in using the Python programming language for research, data analysis, software development, or academic projects. These individuals often work in fields like data science, machine learning, scientific computing, or academia, where complex problem-solving and advanced analytical skills are required. Their expertise in both research methodologies and Python allows them to tackle sophisticated computational tasks and contribute to cutting-edge innovation.
What are popular job titles related to Phd Python jobs in Kentucky? For Phd Python jobs in Kentucky, the most frequently searched job titles are:
What job categories do people searching Phd Python jobs in Kentucky look for? The top searched job categories for Phd Python jobs in Kentucky are:
What cities in Kentucky are hiring for Phd Python jobs? Cities in Kentucky with the most Phd Python job openings:
Genentech rating
8.8
Based on 22 frontline employees who took The Breakroom Quiz
10th of 74 rated pharmaceutical
Job description
Job Summary:
Genentech, a pioneering biotechnology company now part of the Roche Group, is dedicated to developing groundbreaking medicines for serious health challenges. The Principal Supply Chain Data Scientist will lead advanced analytical initiatives to optimize pharmaceutical distribution processes, leveraging data science methodologies and technologies to enhance supply chain strategy and decision-making.
Responsibilities:
• Design, implement, and validate advanced algorithms and predictive models to solve supply chain challenges in a high-pace distribution operation.
• Apply machine learning, statistical methods, and optimization techniques to enhance forecasting, inventory management, and logistics planning.
• Analyze large datasets and business systems to identify trends, patterns, and innovative opportunities using data mining tools and statistical approaches.
• Develop advanced AI-driven tools for improved planning accuracy, distribution efficiency, and warehouse operations.
• Develop and maintain reports and dashboards using Tableau.
• Generate and distribute reports using SQL Reporting Services.
• Develop and implement distribution plans to optimize product movement from manufacturing facilities to customers.
• Create and execute detailed schedules for deliveries, warehouse operations, and related activities.
• Effectively manage warehouse capacity modeling and assessments to ensure accurate and timely insights.
• Conduct space utilization analysis, evaluating how effectively warehouse space is being used and identifying areas for improvement.
• Plan inbound/outbound logistics to meet daily and weekly distribution schedules.
• Plan efficient delivery routes and schedules for cost-effective transportation of medications.
• Analyze the distribution network to identify bottlenecks, optimize routes, and improve overall efficiency and cost-effectiveness.
• Drive the creation of digital twin models for scenario planning and strategic decision-making, ensuring efficient and sustainable supply chain practices.
• Evaluate and propose innovation opportunities through investment modeling and process improvements.
• Serve as a strategic advisor, translating business challenges into actionable, data-driven insights.
• Present findings, recommendations, and strategic plans to senior leadership, aligning advanced analytics with organizational goals.
• Act as the subject matter expert in supply chain analytics, providing guidance across initiatives and projects.
• Manage data governance frameworks, ensuring integrity, accuracy, and compliance with regulations.
• Track key performance indicators (KPIs) such as on-time delivery rates, inventory turns, and order fulfillment rates to identify areas for improvement.
• Analyze performance data to identify issues and implement changes to enhance efficiency and customer service.
• Address disruptions in the distribution process promptly and develop contingency plans for potential risks.
• Regularly review performance metrics and adjust processes for ongoing optimization.
• Use advanced planning systems and AI-driven tools to improve planning accuracy and optimize warehouse operations.
• Create comprehensive documentation and reports to communicate insights and recommendations.
• Ensure compliance with relevant regulations and guidelines related to pharmaceutical distribution and supply chain management.
• Create, implement, and manage data integration workflows using SQL Integration Services.
• Develop multidimensional cubes and tabular models in SQL Analysis Services.
• Ensure data integrity, accuracy, and security across all BI systems.
• Continuously improve BI processes and methodologies to enhance efficiency and effectiveness.
Qualifications:
Required:
• Bachelor's degree in a quantitative or technical field (e.g., Data Science, Supply Chain Management, Logistics, Operations Research, Mathematics, or Computer Science) required.
• Over 10 years of experience in supply chain analytics, business intelligence, or advanced data science roles, with a minimum of 8 years in advanced supply chain analytics.
• Proficiency in Python, SQL, and cloud-based tools with experience in developing machine learning models and optimization algorithms.
• Hands-on experience with advanced statistical and machine learning packages (e.g., scikit-learn, TensorFlow, R).
• Skilled in optimization tools (e.g., Gurobi, CPLEX) and inventory management platforms.
• Deep understanding of supply chain management principles, including forecasting, inventory optimization, logistics planning, and procurement.
• In-depth experience with pharmaceutical distribution requirements, industry standards, and compliance regulations.
• Familiarity with warehouse operations, capacity planning, network design, and space utilization analysis.
• Familiarity with SQL Integration Services, SQL Analysis Services, and SQL Reporting Services.
Preferred:
• Advanced degrees (Master's, PhD) in the same fields strongly preferred, with demonstrated expertise in supply chain analytics.
• Demonstrated track record of implementing analytics within a supply chain context, with pharmaceutical distribution expertise strongly preferred.
Company:
Genentech is a biotechnology research company that specializes in genetic testing and personalized medicines. Founded in 1976, the company is headquartered in South San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.
Genentech, a pioneering biotechnology company now part of the Roche Group, is dedicated to developing groundbreaking medicines for serious health challenges. The Principal Supply Chain Data Scientist will lead advanced analytical initiatives to optimize pharmaceutical distribution processes, leveraging data science methodologies and technologies to enhance supply chain strategy and decision-making.
Responsibilities:
• Design, implement, and validate advanced algorithms and predictive models to solve supply chain challenges in a high-pace distribution operation.
• Apply machine learning, statistical methods, and optimization techniques to enhance forecasting, inventory management, and logistics planning.
• Analyze large datasets and business systems to identify trends, patterns, and innovative opportunities using data mining tools and statistical approaches.
• Develop advanced AI-driven tools for improved planning accuracy, distribution efficiency, and warehouse operations.
• Develop and maintain reports and dashboards using Tableau.
• Generate and distribute reports using SQL Reporting Services.
• Develop and implement distribution plans to optimize product movement from manufacturing facilities to customers.
• Create and execute detailed schedules for deliveries, warehouse operations, and related activities.
• Effectively manage warehouse capacity modeling and assessments to ensure accurate and timely insights.
• Conduct space utilization analysis, evaluating how effectively warehouse space is being used and identifying areas for improvement.
• Plan inbound/outbound logistics to meet daily and weekly distribution schedules.
• Plan efficient delivery routes and schedules for cost-effective transportation of medications.
• Analyze the distribution network to identify bottlenecks, optimize routes, and improve overall efficiency and cost-effectiveness.
• Drive the creation of digital twin models for scenario planning and strategic decision-making, ensuring efficient and sustainable supply chain practices.
• Evaluate and propose innovation opportunities through investment modeling and process improvements.
• Serve as a strategic advisor, translating business challenges into actionable, data-driven insights.
• Present findings, recommendations, and strategic plans to senior leadership, aligning advanced analytics with organizational goals.
• Act as the subject matter expert in supply chain analytics, providing guidance across initiatives and projects.
• Manage data governance frameworks, ensuring integrity, accuracy, and compliance with regulations.
• Track key performance indicators (KPIs) such as on-time delivery rates, inventory turns, and order fulfillment rates to identify areas for improvement.
• Analyze performance data to identify issues and implement changes to enhance efficiency and customer service.
• Address disruptions in the distribution process promptly and develop contingency plans for potential risks.
• Regularly review performance metrics and adjust processes for ongoing optimization.
• Use advanced planning systems and AI-driven tools to improve planning accuracy and optimize warehouse operations.
• Create comprehensive documentation and reports to communicate insights and recommendations.
• Ensure compliance with relevant regulations and guidelines related to pharmaceutical distribution and supply chain management.
• Create, implement, and manage data integration workflows using SQL Integration Services.
• Develop multidimensional cubes and tabular models in SQL Analysis Services.
• Ensure data integrity, accuracy, and security across all BI systems.
• Continuously improve BI processes and methodologies to enhance efficiency and effectiveness.
Qualifications:
Required:
• Bachelor's degree in a quantitative or technical field (e.g., Data Science, Supply Chain Management, Logistics, Operations Research, Mathematics, or Computer Science) required.
• Over 10 years of experience in supply chain analytics, business intelligence, or advanced data science roles, with a minimum of 8 years in advanced supply chain analytics.
• Proficiency in Python, SQL, and cloud-based tools with experience in developing machine learning models and optimization algorithms.
• Hands-on experience with advanced statistical and machine learning packages (e.g., scikit-learn, TensorFlow, R).
• Skilled in optimization tools (e.g., Gurobi, CPLEX) and inventory management platforms.
• Deep understanding of supply chain management principles, including forecasting, inventory optimization, logistics planning, and procurement.
• In-depth experience with pharmaceutical distribution requirements, industry standards, and compliance regulations.
• Familiarity with warehouse operations, capacity planning, network design, and space utilization analysis.
• Familiarity with SQL Integration Services, SQL Analysis Services, and SQL Reporting Services.
Preferred:
• Advanced degrees (Master's, PhD) in the same fields strongly preferred, with demonstrated expertise in supply chain analytics.
• Demonstrated track record of implementing analytics within a supply chain context, with pharmaceutical distribution expertise strongly preferred.
Company:
Genentech is a biotechnology research company that specializes in genetic testing and personalized medicines. Founded in 1976, the company is headquartered in South San Francisco, USA, with a team of 10001+ employees. The company is currently Late Stage.
What Genentech employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Genentech
Sourced by ZipRecruiter
A member of the Roche Group, Genentech has been at the forefront of the biotechnology industry for more than 40 years, using human genetic information to develop novel medicines for serious and life-threatening diseases. Genentech has multiple therapies on the market for cancer & other serious illnesses. Please take this opportunity to learn about Genentech where we believe that our employees are our most important asset & are dedicated to remaining a great place to work.
Industry
Scientific research and development services
Company size
10,000+ Employees
Headquarters location
South San Francisco, CA, US
Year founded
1976