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Summer Data Science Physics Jobs (NOW HIRING)

The Research Data Science team builds innovative solutions for iSpot's audience measures ... physics, social sciences, or other quantitative discipline. ● Relevant work experience is ...

The Research Data Science team builds innovative solutions for iSpot's audience measures ... physics, social sciences, or other quantitative discipline. • Relevant work experience is ...

ABOUT THE DATA TEAM The Data Science team at GenLogs transforms raw observational data from the ... You bring a background in engineering, computer science, physics, applied math, or another hard ...

... Data Science, Physics, Computer Science, Operations Research, Economics, Engineering or related quantitative field, PhD preferred - 5-7 years experience applying predictive analytics and modeling to ...

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems ... D. in quantitative fields (e.g., Statistics, Math, Computer Science, Physics, Economics ...

D. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations Research, or related technical field with 6+ years of relevant industry experience; OR M.S./B.S. with 8+ years ...

D. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations Research, or related technical field with 6+ years of relevant industry experience; OR M.S./B.S. with 8+ years ...

Data Science * Statistics * Mathematics * Engineering ... Economics * Physics * Or a related quantitative field. We may use artificial intelligence (AI ...

D. in Data Science, Machine Learning, Computer Science, Physics, Mathematics, Operations Research, or related technical field with 6+ years of relevant industry experience; OR M.S./B.S. with 8+ years ...

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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 Science Intern

iSpot

Bellevue, WA • Hybrid

$35/hr

Full-time, Part-time, Internship

Re-posted 2 days ago


Job description

Immigration / Work Authorization Notice: Applicants must be currently authorized to work in the United States. iSpot is not able to sponsor or take over sponsorship of an employment visa for this position at this time.

iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle's hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great.

What You'll Be Part Of

An iSpot Research Data Science Intern is a great opportunity to help iSpot push the boundaries on what is measurable in the TV viewing and advertising space. The Research Data Science team builds innovative solutions for iSpot's audience measures, attribution and lift analytics, creative testing, and artificial intelligence implementations. After developing new methodologies and building prototypes, we work with our product and engineering teams to scale our models to satisfy the needs of brands, publishers, networks, and agencies in a constantly evolving marketing landscape.

Potential Responsibilities:

• Data Analysis and Modeling: Conduct in-depth data analysis and build advanced statistical models to extract insights from large viewing and demographic datasets.
• Machine Learning Model Development: Develop, train, and deploy state-of-the-art machine learning models to solve a variety of measurement problems.
• Data Pipeline Development: Work with our Engineering teams to design and implement efficient data pipelines to collect, process, and transform data from various sources.
• Research and Innovation: Stay up-to-date with the latest data science techniques, tools, and technologies, and explore novel approaches to solve complex challenges.
Qualifications and Education Requirements:
● Progress toward a degree in mathematics, economics, statistics, computer science, physics, social sciences, or other quantitative discipline.
● Relevant work experience is preferred.
Preferred Skills:
● Technical understanding of machine learning, statistics, data science, and related fields
● Proficient user in several quantitative software tools, particularly Python, R, and/or SQL; willingness to learn new tools as needed
● Expert at wrangling data and conducting thorough data analyses
● Pragmatic, team-oriented; builds rapport and respect
● Strong communication, writing, and critical thinking skills; attention to detail

Target cash compensation range: $35.00USD/hour

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot's equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency.

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

#LI-Hybrid

If you don't feel you met every single requirement for the role, don't rule yourself out. Please apply anyway!

iSpot is an equal opportunity employer. All applicants will receive consideration for employment without regard to race, ethnicity, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please contact our HR team.

California Residents applying for positions at iSpot can access our California Consumer Privacy Act here.