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Summer Data Science Physics Jobs (NOW HIRING)

D. in a quantitative discipline (Statistics, Computer Science, Physics, Electrical Engineering, etc.). • Experience developing within cloud-based platforms (e.g., AWS, Azure, or GovCloud). • ...

We're seeking a Data Scientist who combines technical expertise with strong interpersonal skills to ... Bachelor's degree in mathematics, statistics, computer science, physics, or a STEM related field ...

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Progress toward a degree in mathematics, economics, statistics, computer science, physics, social ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... S. in Computer Science, Computational Physics, Operations Research, Geospatial Sciences, Remote ...

As a Data Scientist, you will build fraud detection models and advance products in financial risk ... Required : • Bachelor's, Master's, or PhD in Statistics, Computer Science, Physics, Mathematics ...

Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. * Engage with other developers frequently to share relevant knowledge, opinions, and ...

Ph.D. in a quantitative discipline (Statistics, Computer Science, Physics, Electrical Engineering ... Advanced experience with data visualization tools (e.g., Tableau, PowerBI, or R/Shiny

Assess the requirements for data science research from Applied Physics and the Advanced Propulsion Laboratory. * Engage with other developers frequently to share relevant knowledge, opinions, and ...

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Summer Data Science Physics information

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often focus on the most impactful features or data subsets to optimize models and improve efficiency.

What is the difference between Summer Data Science Physics vs Summer Data Science Engineering?

AspectSummer Data Science PhysicsSummer Data Science Engineering
Required CredentialsTypically requires physics or data science coursework, basic programming skillsRequires engineering fundamentals, programming, and data analysis skills
Work EnvironmentResearch labs, academic institutions, tech companiesManufacturing, product development, tech firms
Industry UsageResearch, academia, tech industryEngineering, manufacturing, software development
Common Search IntentComparing physics-focused data science roles with engineering data science rolesUnderstanding differences between physics and engineering data science internships

Summer Data Science Physics roles focus on applying data analysis within physics research or academic settings, often emphasizing theoretical understanding. In contrast, Summer Data Science Engineering positions are geared toward practical engineering applications, product development, and manufacturing. Both roles require programming skills and data analysis, but their industry focus and work environments differ significantly.

What types of projects or research tasks can I expect to work on in a Summer Data Science Physics role?

In a Summer Data Science Physics position, you'll likely engage in projects that involve analyzing large datasets from physics experiments or simulations. Common tasks include data cleaning, statistical analysis, building predictive models, and visualizing results to support ongoing research. You'll often collaborate with physicists and data scientists, contributing to the interpretation of experimental data or the development of computational tools. This role offers a fast-paced, collaborative environment where you'll gain hands-on experience with both physics concepts and practical data science techniques.

Does NASA hire data scientists?

Yes, NASA hires data scientists to analyze large datasets related to space missions, climate, and engineering. These roles often require skills in programming, statistical analysis, and experience with tools like Python, R, or MATLAB. Data scientists at NASA contribute to research, mission planning, and data-driven decision making.

What are the key skills and qualifications needed to thrive as a Summer Data Science Physics intern, and why are they important?

To thrive as a Summer Data Science Physics intern, you need a solid background in physics, statistics, and programming, typically supported by coursework or a degree in physics, data science, or a related field. Familiarity with programming languages such as Python, data analysis libraries (e.g., NumPy, Pandas), and data visualization tools is often required. Strong analytical thinking, problem-solving abilities, and effective communication skills help you interpret complex data and present findings clearly. These skills are crucial for extracting meaningful insights from scientific data and contributing to research projects in a collaborative environment.

What is a Summer Data Science Physics job?

A Summer Data Science Physics job is a temporary, usually internship-based position where students or recent graduates apply data science techniques to solve problems in physics. These roles typically involve working with large datasets, coding in languages like Python, and using statistical or machine learning methods to analyze experimental or simulation data. The goal is to gain hands-on experience at the intersection of physics and data science, often contributing to research projects or industry applications. Such positions are common at universities, research labs, and tech companies during the summer months, providing valuable exposure to both fields.

Is 30 too late for data science?

Age is not a strict barrier for a data science career, and many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Can data scientists make $300k?

Data scientists, including those working in physics-related roles, can earn $300,000 or more at senior levels or in high-paying industries such as finance or technology, especially with extensive experience, advanced skills in machine learning, and strong domain expertise. Achieving this salary often requires advanced degrees, specialized knowledge, and a track record of impactful projects.
What cities are hiring for Summer Data Science Physics jobs? Cities with the most Summer Data Science Physics job openings:
What are the most commonly searched types of Data Science Physics jobs? The most popular types of Data Science Physics jobs are:
What states have the most Summer Data Science Physics jobs? States with the most job openings for Summer Data Science Physics jobs include:
Data Scientist - Predictive Analytics, Expert

Data Scientist - Predictive Analytics, Expert

Pacific Gas and Electric Company

Oakland, CA • On-site

$140K - $207K/yr

Full-time

Re-posted 14 days ago


Pacific Gas and Electric Company rating

8.2

Company rating: 8.2 out of 10

Based on 17 frontline employees who took The Breakroom Quiz


Job description

Requisition ID # 167321
Job Category: Accounting / Finance
Job Level: Individual Contributor
Business Unit: Electric Engineering
Work Type: Hybrid
Job Location: Oakland
Department Overview
The System Performance, Reliability and Resiliency Strategy team within the overall Electric Transmission and Distribution Engineering organization is responsible for planning, organizing, and managing the resources necessary to successfully execute PG&E's Electric Reliability Strategy and initiatives. This team of forward-thinking individuals will be tasked with deploying technology and infrastructure and influencing the organization to achieve the company's reliability goals. The team is responsible for implementing programs required to modernize the electric grid allowing for safe, resilient and efficient operations. The team participates in a cross functional team of internal and consulting participants being tasked with leading the transition of a project from development and testing to being operational for each phase of each project.
Position Summary
Within the System Performance, Reliability and Resiliency Strategy team, this position reports to the Senior Manager of Reliability Analytics and is responsible for developing advanced data science models and industry-leading anomaly detection techniques to identify potential failures and enhance the reliability of the electric transmission and distribution grid.
In this role, the successful candidate will be uniquely positioned at the forefront of utility industry analytics. Working as part of cross-functional teams, including data engineers, data scientists, technologists, and subject matter experts - this individual will lead the development of data science capabilities that could lead to paradigm changes in how the utility operates.
This position is hybrid, working from your remote office and your assigned work location based on business need. The assigned work location will be within the PG&E Service Territory.
PG&E is providing the salary range that can reasonably be expected for this position at the time of the job posting. This salary range is specific to the locality of the job. The actual salary paid to an individual will be based on multiple factors, including, but not limited to, internal equity, specific skills, education, licenses or certifications, experience, market value, and geographic location. The decision will be made on a case-by-case basis related to these factors. This job is also eligible to participate in PG&E's discretionary incentive compensation programs.
Bay Area - $140,000 - $207,900
And/or
California - $133,000 - $198,000
Job Responsibilities
  • Lead research and development of state-of-the-art methodologies to detect potential system failures and improve the reliability of the electric transmission and distribution grid.
  • Applies data science/ machine learning /artificial intelligence methods to develop defensible and reproducible models,
  • Serves as the technical lead for the development of predictive/reliability analytics models.
  • Develops python codes for data processing and data science model developments (e.g., ML/AI models, advanced statistical models)
  • Documents datasets, modeling processes, and result to ensure transparency, reproducibility, and defensibility.
  • Contribute to the development of data science strategies aligned with system performance, reliability, and resiliency team goals.
  • Communicate technical concepts and model results to internal/external stakeholders.
  • Assesses business implications associated with modeling assumptions, inputs, methodologies, technical implementation, analytic procedures and processes, and advanced data analysis.
  • Works with sponsor departments and company subject matter experts to understand application and potential of data science solutions that create value.
  • Act as peer reviewer of complex models

Qualifications
Minimum:
  • Bachelor's Degree in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.
  • Experience in Data Science, 6 years or no experience, if possess Doctoral Degree or higher in Data Science, Machine Learning, Computer Science, Physics, Econometrics or Economics, Engineering, Mathematics, Applied Sciences, Statistics, or equivalent field.

Desired:
  • Doctorate degree with 5+ years or Master's degree with 8+ years in Electrical Engineering, Mechanical Engineering, Operations Research, Transportation Engineering, Physics, Applied Sciences, Statistics, or job-related discipline or equivalent experience
  • Relevant industry (electric or gas utility, renewable energy, analytics consulting, etc.) experience
  • Active participation in professional communities related to utility reliability, such as IEEE Power and Energy Society (PES), is a plus.
  • Strong foundation in statistics, machine learning (ML), and artificial intelligence (AI).
  • Hands-on and theoretical experience in developing and deploying data science and ML models using Python.
  • Proven ability to formulate and solve unstructured, complex problems using data-driven approaches.
  • Proficiency in working with large datasets, including structured and unstructured data from diverse sources.
  • Excellent communication skills, with the ability to explain technical concepts to non-technical audiences.
  • Ability to develop, coach and teach career level data scientists in data science/artificial intelligence/machine learning techniques and technologies

Purpose, Virtues and Stands
Our Purpose explains "why" we exist:
  • Delivering for our hometowns
  • Serving our planet
  • Leading with love

Our Virtues capture "who" we need to be:
  • Trustworthy
  • Empathetic
  • Curious
  • Tenacious
  • Nimble
  • Owners

Our Stands are "what" we will achieve together:
  • Everyone and everything is always safe
  • Catastrophic wildfires shall stop
  • It is enjoyable to work with and for PG&E
  • Clean and resilient energy for all
  • Our work shall create prosperity for all customers and investors

More About Our Company
EEO
Pacific Gas and Electric Company is an Equal Employment Opportunity employer that actively pursues and hires a workforce that reflects the hometowns we serve. All qualified applicants will receive consideration for employment without regard to race, color, national origin, ancestry, sex, age, religion, physical or mental disability status, medical condition, protected veteran status, marital status, pregnancy, sexual orientation, gender, gender identity, gender expression, genetic information or any other factor that is not related to the job.
Employee Privacy Notice The California Consumer Privacy Act (CCPA) goes into effect on January 1, 2020. CCPA grants new and far-reaching privacy rights to all California residents. The law also entitles job applicants, employees and non-employee workers to be notified of what personal information PG&E collects and for what purpose. The Employee Privacy Notice can be accessed through the following link: Employee Privacy Notice
PG&E will consider qualified applicants with arrest and conviction records for employment in a manner consistent with all state and local laws.

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