... classification, causal inference, clustering) • Experience with cloud data/analytics solutions (e.g., Azure or AWS) • Experience managing and coaching a team, with strong written/verbal ...
... classification, causal inference, clustering) • Experience with cloud data/analytics solutions (e.g., Azure or AWS) • Experience managing and coaching a team, with strong written/verbal ...
Student loan management resources * Backup care * DACA reimbursement Preferred Qualifications ... Familiarity with experiment design, causal inference, and translating results into business actions
Student loan management resources * Backup care * DACA reimbursement Preferred Qualifications ... Familiarity with experiment design, causal inference, and translating results into business actions
... causal inference, clustering) * Experience with cloud data/analytics solutions (e.g., Azure or AWS ... Experience managing and coaching a team, with strong written/verbal communication skills and ...
... causal inference, clustering) * Experience with cloud data/analytics solutions (e.g., Azure or AWS ... Experience managing and coaching a team, with strong written/verbal communication skills and ...
... causal inference, clustering) * Experience with cloud data/analytics solutions (e.g., Azure or AWS ... Experience managing and coaching a team, with strong written/verbal communication skills and ...
... causal inference, clustering) * Experience with cloud data/analytics solutions (e.g., Azure or AWS ... Experience managing and coaching a team, with strong written/verbal communication skills and ...
... capacity management, deployment tradeoffs, and network performance. * Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn ...
... capacity management, deployment tradeoffs, and network performance. * Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn ...
... capacity management, deployment tradeoffs, and network performance. * Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn ...
... capacity management, deployment tradeoffs, and network performance. * Experimentation & Measurement Excellence: Oversee experimentation design, causal inference, and an internal test-and-learn ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
... causal inference. Search & Discovery ML : The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search ...
Familiarity with experiment design / causal inference and translating results into business actions ... management resources, and access to other educational opportunities. You will also have access to ...
Familiarity with experiment design / causal inference and translating results into business actions ... management resources, and access to other educational opportunities. You will also have access to ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... management resources, and access to other educational opportunities. You will also have access to ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... management resources, and access to other educational opportunities. You will also have access to ...
Familiarity with experiment design / causal inference and translating results into business actions ... management resources, and access to other educational opportunities. You will also have access to ...
Familiarity with experiment design / causal inference and translating results into business actions ... management resources, and access to other educational opportunities. You will also have access to ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... management resources, and access to other educational opportunities. You will also have access to ...
... causal inference) * Experience with data visualization tools (e.g., Tableau, Power BI, or similar ... management resources, and access to other educational opportunities. You will also have access to ...
Manager Causal Inference information
What does a manager causal inference do?
A Manager Causal Inference leads teams that analyze data to determine cause-and-effect relationships, often in business, healthcare, or technology settings. They design experiments or use statistical methods to understand how different factors influence outcomes, helping organizations make data-driven decisions. This role typically involves managing projects, overseeing analysts or data scientists, and communicating findings to stakeholders. Strong expertise in statistics, data analysis, and leadership is essential for success in this position.
What are the key skills and qualifications needed to thrive as a manager causal inference?
To thrive as a Manager of Causal Inference, you need a deep understanding of statistics, econometrics, and experimental design, typically supported by an advanced degree in a quantitative field. Proficiency with data analysis tools such as R, Python, SQL, and specialized causal inference libraries, along with experience using data visualization and project management platforms, is crucial. Strong leadership, communication, and critical thinking skills help you effectively guide teams and translate complex findings to stakeholders. These skills ensure rigorous, actionable insights that drive strategic decision-making and organizational impact.
How does a manager causal inference typically collaborate with cross-functional teams to drive impactful business insights?
Managers of Causal Inference frequently work alongside data scientists, product managers, engineers, and business leaders to design and execute experiments that reveal the true impact of business decisions. They translate complex statistical findings into actionable recommendations, ensuring stakeholders understand both the methodology and implications. Regularly, they lead discussions on experiment design, data collection strategies, and result interpretation, fostering a culture of evidence-based decision-making across the organization.
What are the most commonly searched types of Causal Inference jobs in Tennessee?
The most popular types of Causal Inference jobs in Tennessee are:
What are popular job titles related to Manager Causal Inference jobs in Tennessee?
For Manager Causal Inference jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Manager Causal Inference jobs in Tennessee look for?
The top searched job categories for Manager Causal Inference jobs in Tennessee are:
What cities in Tennessee are hiring for Manager Causal Inference jobs?
Cities in Tennessee with the most Manager Causal Inference job openings:
Full-time
Re-posted 17 days ago
Starbucks rating
6.7
Based on 3,620 frontline employees who took The Breakroom Quiz
3rd of 16 rated cafes
Job description
Job Summary:
Starbucks is a company known for celebrating coffee and fostering connections. They are seeking a Data Science Manager to lead a team of data scientists and analysts, focusing on building models and applying advanced analytics to solve business problems while ensuring best practices and scalability in insights and machine learning solutions.
Responsibilities:
• Lead and develop a high-performing team by coaching, creating development plans, and building a culture of strong execution, collaboration, and continuous learning.
• Drive end-to-end data science delivery from problem framing and data preparation through modeling, performance assessment, and operationalization of insights/models.
• Set and scale best practices across coding standards, version control, documentation, data security, and analytics/engineering practices—removing roadblocks and aligning cross-functional partners.
Qualifications:
Required:
• BA/BS (or equivalent experience)
• 5–7+ years of experience in data science, analytics, or a closely related field
• Proficiency with Python or R, SQL, and relational databases
• Working knowledge of machine learning/statistical techniques (e.g., regression, decision trees, classification, causal inference, clustering)
• Experience with cloud data/analytics solutions (e.g., Azure or AWS)
• Experience managing and coaching a team, with strong written/verbal communication skills and attention to detail
Preferred:
• MS in a quantitative field (e.g., Statistics, Math, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science) or equivalent advanced experience
• 8+ years managing a small team (approximately 2–4 people) and developing technical talent
• Experience with production ML practices (shared codebases, package creation, repositories, SDLC best practices), plus distributed processing/modern platforms (e.g., Databricks or similar)
• Experience with hyperparameter tuning and ongoing model performance monitoring (measurement, drift, stability)
Company:
Starbucks is a restaurant chain that serves handcrafted ready-to-drink beverages, including coffee, tea, juices, and snack food items. Founded in 1971, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.
Starbucks is a company known for celebrating coffee and fostering connections. They are seeking a Data Science Manager to lead a team of data scientists and analysts, focusing on building models and applying advanced analytics to solve business problems while ensuring best practices and scalability in insights and machine learning solutions.
Responsibilities:
• Lead and develop a high-performing team by coaching, creating development plans, and building a culture of strong execution, collaboration, and continuous learning.
• Drive end-to-end data science delivery from problem framing and data preparation through modeling, performance assessment, and operationalization of insights/models.
• Set and scale best practices across coding standards, version control, documentation, data security, and analytics/engineering practices—removing roadblocks and aligning cross-functional partners.
Qualifications:
Required:
• BA/BS (or equivalent experience)
• 5–7+ years of experience in data science, analytics, or a closely related field
• Proficiency with Python or R, SQL, and relational databases
• Working knowledge of machine learning/statistical techniques (e.g., regression, decision trees, classification, causal inference, clustering)
• Experience with cloud data/analytics solutions (e.g., Azure or AWS)
• Experience managing and coaching a team, with strong written/verbal communication skills and attention to detail
Preferred:
• MS in a quantitative field (e.g., Statistics, Math, Computer Science, Engineering, Economics, Psychology, Quantitative Social Science) or equivalent advanced experience
• 8+ years managing a small team (approximately 2–4 people) and developing technical talent
• Experience with production ML practices (shared codebases, package creation, repositories, SDLC best practices), plus distributed processing/modern platforms (e.g., Databricks or similar)
• Experience with hyperparameter tuning and ongoing model performance monitoring (measurement, drift, stability)
Company:
Starbucks is a restaurant chain that serves handcrafted ready-to-drink beverages, including coffee, tea, juices, and snack food items. Founded in 1971, the company is headquartered in Seattle, USA, with a team of 10001+ employees. The company is currently Late Stage.
What Starbucks employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Starbucks
Sourced by ZipRecruiter
Starbucks Corporation is an American multinational chain of coffeehouses and roastery reserves. It is one of the largest coffeehouse chains in the world. Starbucks was founded in Seattle, Washington in 1971 by Jerry Baldwin, Zev Siegl, and Gordon Bowker. The company's initial focus was on selling whole coffee beans and coffee-making equipment. Over the years, Starbucks has expanded its operations and become known for its distinctive coffeehouse atmosphere and high-quality coffee products. The company offers a wide range of beverages, including various coffee-based drinks, teas, hot chocolates, and other specialty drinks. Starbucks also serves a variety of food items such as pastries, sandwiches, salads, and snacks. One of the key factors that set Starbucks apart from other coffee chains is its commitment to providing a unique customer experience. Starbucks locations are designed to be comfortable and welcoming, often featuring cozy seating areas and free Wi-Fi access. The company aims to create a "third place" between home and work where customers can relax, socialize, or work while enjoying their favorite beverages. One of the key factors that set Starbucks apart from other coffee chains is its commitment to providing a unique customer experience. Starbucks locations are designed to be comfortable and welcoming, often featuring cozy seating areas and free Wi-Fi access. The company aims to create a "third place" between home and work where customers can relax, socialize, or work while enjoying their favorite beverages. One of the key factors that set Starbucks apart from other coffee chains is its commitment to providing a unique customer experience. Starbucks locations are designed to be comfortable and welcoming, often featuring cozy seating areas and free Wi-Fi access. The company aims to create a "third place" between home and work where customers can relax, socialize, or work while enjoying their favorite beverages. In addition to its traditional coffeehouses, Starbucks has expanded its brand to include different store formats. This includes drive-thru locations, express stores, and even upscale Reserve Roasteries and Reserve Bars that offer a more immersive coffee experience. Starbucks is also known for its ethical sourcing practices. The company has implemented programs such as Coffee and Farmer Equity (C.A.F.E.) Practices, which promote environmentally friendly and socially responsible coffee production. Starbucks has a commitment to ethically sourcing its coffee beans and has made efforts to support sustainable farming practices and improve the livelihoods of coffee farmers. The Starbucks brand has a global presence, with thousands of stores in countries around the world. It has become a symbol of premium coffee and a popular destination for coffee lovers worldwide. The company's success has made it an iconic brand and a significant player in the global coffee industry.
Industry
Food services and drinking places and restaurants
Company size
10,000+ Employees
Headquarters location
Seattle, WA, US