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Phd In Statistics Jobs in Texas (NOW HIRING)

... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas: Deep familiarity ...

... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas: Deep familiarity ...

... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas: Deep familiarity ...

... PhD in Statistics, Economics, Mathematics, Computer Science, Engineering, Data Science, or a related quantitative discipline and experience in one or more of the following areas: Deep familiarity ...

Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: * Coding knowledge and experience with several languages:

Master's or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools: * Coding knowledge and experience with several languages:

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Phd In Statistics information

What is the difference between Phd In Statistics vs Data Scientist?

AspectPhd In StatisticsData Scientist
Required CredentialsTypically a PhD in Statistics or related fieldOften a bachelor's or master's degree in a quantitative field; some roles prefer a PhD
Work EnvironmentAcademic, research institutions, or specialized analytics teamsCorporate, tech companies, or consulting firms
Industry UsageResearch, academia, government, and industry R&DBusiness analytics, product development, and data-driven decision making
Common Search & ComparisonYesYes

While a Phd In Statistics focuses on advanced research, theoretical development, and academic roles, Data Scientists apply statistical and machine learning techniques to solve practical business problems. Both roles require strong analytical skills, but Data Scientists often work in more applied, industry-focused environments, whereas PhD holders may pursue research or academic careers.

What is the highest paying job with a statistics degree?

The highest paying jobs with a statistics degree often include roles such as data scientist, quantitative analyst, or actuarial scientist, with salaries exceeding $100,000 annually. Senior positions in finance, technology, or consulting firms tend to offer the highest compensation, especially for those with advanced skills in machine learning, programming, and statistical modeling.

How much can you make with a PhD in statistics?

A PhD in statistics can lead to high-paying roles such as data scientist, quantitative analyst, or research scientist, with salaries typically ranging from $90,000 to over $150,000 annually depending on experience, industry, and location. Advanced skills in programming, statistical software, and data analysis increase earning potential in this field.

Is getting a PhD in statistics worth it?

A PhD in statistics prepares individuals for advanced research, academia, and data science roles that require deep analytical skills and expertise in statistical methods. It can lead to higher-level positions and increased earning potential but involves significant time and financial investment. The decision depends on career goals and the demand for specialized statistical knowledge in the desired industry.

What can I do with PhD in statistics?

A PhD in statistics qualifies individuals for advanced roles such as data scientist, quantitative analyst, biostatistician, or research scientist. These positions often involve data analysis, modeling, and interpretation using statistical software like R or SAS, and may require collaboration across industries such as healthcare, finance, or technology.

Lead Data Scientist, Autonomous Driving

Avride

Austin, TX • On-site

Full-time

Posted 2 days ago


Job description

Job Summary:
Avride is focused on advancing autonomous driving technology and is seeking a Lead Data Scientist to build and lead their analytics function. The role involves evaluating technology performance, leading a team of analysts, and producing actionable insights through experimentation and data analysis.
Responsibilities:
• Understand the technology deeply. Go deep into autonomous driving technology across behavior and hardware. Evaluate platform health and system behavior, and define the right metrics and metric hierarchy to quantify technology quality.
• Help build and lead the team. Contribute to team formation, take part in hiring and leveling up analysts, and set direction for an evaluation focus area while collaborating with technology leaders and with teams that build data infrastructure and analytics tools.
• Be hands-on with experiments. Design, run, and interpret experiments using solid statistical methods. Be ready to analyze results yourself and translate them into well-supported decisions.
• Build and automate analysis. Collaborate with data engineers and backend developers to assemble datasets and productionize analysis pipelines that automate recurring computations with attention to performance and reliability.
Qualifications:
Required:
• 4+ years in analytics for a large-scale or complex technology product.
• Strong background in statistical reasoning and methods for evaluating change and uncertainty.
• Strong Python and SQL; you can independently run experiments and ship analyses and pipelines end to end.
• Proven technical leadership, mentoring, and hiring experience in analytics.
Preferred:
• Formal training in statistics (for example, MS or PhD in Statistics, Applied Statistics, Biostatistics, Econometrics, or a quantitative field with rigorous statistical coursework).
• Familiarity with the modern data stack and experience in data engineering.
• Background in autonomy or other technologically intensive domains.
Company:
Avride is a developer and operator of autonomous vehicles and delivery robots. Founded in 2017, the company is headquartered in Austin, USA, with a team of 201-500 employees. The company is currently Growth Stage.