ZipRecruiter

Log In

1

Overnight Data Science Physics Jobs (NOW HIRING)

Roblox

Principal Data Scientist - Safety

San Mateo, CA · On-site

WHY DATA SCIENCE & ANALYTICS? The Data Science & Analytics organization's mission is to increase ... Advanced Degree and/or PhD in Statistics, Computer Science, Physics, Applied Math, Economics, or ...

Equifax, Inc.

Data Scientist - Career

Atlanta, GA · On-site

... 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 ...

Databricks

Staff Data Scientist

San Francisco, CA

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 ...

OpenX

Staff Data Scientist

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 ...

DEUNA

Data Science intern

San Francisco, CA · On-site

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

OpenX

Staff Data Scientist

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 ...

Equifax, Inc.

Data Scientist - Specialist

Alpharetta, GA · On-site

Master's degree or higher in Mathematics, Statistics, Data Science, Physics, Computer Science, Operations Research, Economics, Engineering or related quantitative field, PhD preferred * 7-10 years of ...

OpenX

Staff Data Scientist

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 ...

OpenX

Staff Data Scientist

New York, NY · Remote

Ph.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+ ...

OpenX

Staff Data Scientist

New York, NY · On-site +1

Ph.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+ ...

OpenX

Staff Data Scientist

New York, NY · On-site

Ph.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+ ...

iSpot

Research Data Scientist 1

Bellevue, WA · Remote

$95K - $106K/yr

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Degree in mathematics, economics, statistics, computer science, physics, social sciences, or other ...

iSpot

Research Data Scientist 1

Bellevue, WA · On-site

$95K - $106K/yr

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Degree in mathematics, economics, statistics, computer science, physics, social sciences, or other ...

next page

Showing results 1-20

All JobsOvernight Data Science Physics Jobs

Overnight Data Science Physics information

Can data scientists make $300k?

Data scientists, including those working in specialized fields like physics or with advanced skills in machine learning and big data, can earn $300,000 or more at senior levels or in high-paying industries such as finance or technology. Achieving this salary typically requires extensive experience, advanced degrees, and proficiency with tools like Python, R, and cloud platforms. Entry-level or mid-career data scientists usually earn less than this amount.

Can a physics major be a data scientist?

Yes, a physics major can become a data scientist, as the field values strong analytical, mathematical, and programming skills often developed in physics programs. Additional knowledge of data analysis tools like Python, R, and machine learning techniques can enhance their qualifications for data science roles.

Is 40 too late for data science?

Age is not a barrier to entering data science, including roles like overnight data science positions. Success depends on skills, experience, and continuous learning; many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools.

What is the difference between Overnight Data Science Physics vs Data Analyst?

AspectOvernight Data Science PhysicsData Analyst
Required CredentialsDegree in Physics, Data Science, or related field; programming skillsBachelor's in Statistics, Economics, or related field; analytical skills
Work EnvironmentTech companies, research labs, finance firms; often shift-basedCorporate offices, consulting firms; regular business hours
Industry UsageData-driven research, modeling, and simulation in physics and techBusiness insights, reporting, and data visualization across industries
Search & Comparison IntentUnderstanding job differences, qualifications, or shift workCareer planning, role comparison, or job requirements

Overnight Data Science Physics roles focus on applying physics principles to data modeling, often requiring advanced technical skills and shift work. Data Analysts typically handle business data analysis during regular hours, emphasizing reporting and visualization. Both roles involve data handling but differ in industry focus, work hours, and required expertise.

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 features. Data scientists often focus on the most impactful features or data subsets to optimize model performance and reduce complexity.
More about Overnight Data Science Physics jobs
What cities are hiring for Overnight Data Science Physics jobs? Cities with the most Overnight 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 Overnight Data Science Physics jobs? States with the most job openings for Overnight Data Science Physics jobs include:
What job categories do people searching Overnight Data Science Physics jobs look for? The top searched job categories for Overnight Data Science Physics jobs are:
Overnight Data Science Physics jobs near you
Infographic showing various Overnight Data Science Physics job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 20% Full Time, and 79% Part Time. Highlights an 90% Physical, and 10% Remote job distribution.
Data Scientist, Finance Forecasting

Data Scientist, Finance Forecasting

ClickHouse

San Francisco, CA

Other

Posted 17 days ago

Job description

ClickHouse is the fastest open-source analytical database in the world, processing billions of rows per second for thousands of organizations. As we scale our cloud business, the decisions that shape pricing, capacity planning, and go-to-market strategy need to be grounded in rigorous quantitative modeling, and that capability is being built from the ground up.

We're hiring a founding Data Scientist to build ClickHouse's Finance forecasting and measurement capability from the ground up. You'll own and build the forecasting models, causal measurement programs, and analytical frameworks that directly shape how leadership plans the business. You'll define the approach, build the infrastructure, and set the standard for how data science operates here.

Hybrid: We intend to fill this role in the San Francisco Bay Area, and expect this position to go into one of our Bay Area offices, Menlo Park and San Francisco, 1-2x per week. 

What You'll Be Doing:
  • Own and build production revenue forecasting end-to-end: model development, backtesting, deployment, monitoring, and iteration
  • Build forecasting systems that account for the dynamics of usage-based pricing, consumption patterns, and customer lifecycle across our cloud platform
  • Design and implement causal measurement frameworks to quantify the revenue impact of product launches, pricing changes, and GTM motions
  • Establish backtesting discipline and accuracy tracking as standing Finance metrics, making forecast quality visible and continuously improving
  • Contribute to shared analytics infrastructure and internal tooling that accelerates data science workflows across the organization
  • Translate model outputs into clear, actionable recommendations for Finance, Sales, and executive leadership
  • Partner with Data Engineering, Revenue Operations, and Product to build the feature pipelines and data foundations your models depend on
What You Bring Along:
  • Has an advanced degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Physics, Economics) or equivalent depth through production experience
  • Hands-on experience building and deploying ML and statistical systems, with meaningful time spent on forecasting or causal inference in production
  • Has deep applied statistics foundations, including comfort with time-series methods, state-space models, hierarchical approaches, or causal inference techniques
  • Is highly proficient in Python and SQL, with experience productionizing models in cloud-scale data environments
  • Has worked with modern analytical platforms such as ClickHouse, Snowflake, BigQuery, or Spark
  • Has experience forecasting consumption-based or usage-billed businesses (cloud, API, marketplace)
  • Has a bias toward action in ambiguous, early-stage environments and is comfortable defining the problem, not just solving it
  • Communicates clearly with executive stakeholders and can translate complex modeling work into actionable business recommendations
  • Is fluent with AI tools and workflows, including LLMs and AI coding assistants, and applies them effectively in analytical work
  • Is comfortable taking ownership of open-ended problems and building new functions from scratch

Apply