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Factor Analysis Jobs (NOW HIRING)

Our ideal candidate will leverage their cyberspace intelligence experience to conduct open / all-source research, network vulnerability analysis, and critical factor analysis in support of cyberspace ...

Data Analyst I

Signal Hill, CA · On-site +1

$114K - $140K/yr

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

$25 - $30/hr

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques, such as calculus, factor ...

System Support Analyst

Long Beach, CA · On-site +1

$25 - $30/hr

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques, such as calculus, factor ...

$25 - $30/hr

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques, such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination. Highly complex mathematical and statistical techniques such as calculus, factor ...

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Factor Analysis information

What is a factor job?

A factor analysis job involves applying statistical techniques to identify underlying variables, or factors, that explain patterns in data. Professionals in this role often work with data analysis software like SPSS or R and require strong analytical skills to interpret complex datasets for research or business insights.

What is factor analysis?

Factor analysis is a statistical technique used to identify underlying patterns or factors within a set of observed variables. It helps researchers reduce data complexity by grouping related variables together, making it easier to interpret large datasets. This method is commonly used in psychology, social sciences, and market research to uncover latent constructs or dimensions that explain correlations among observed measures. Factor analysis can guide the creation of questionnaires, scales, or help in data reduction for further analysis.

What are some common challenges faced by professionals conducting factor analysis, and how can they be addressed?

Professionals performing factor analysis often encounter challenges such as determining the appropriate number of factors to retain and ensuring the quality of data (e.g., sample size and variable selection). Another common issue is interpreting complex factor loadings, which can make it difficult to assign meaningful labels to identified factors. These challenges can be addressed by following best practices such as conducting parallel analysis, using scree plots, ensuring adequate sample sizes, and consulting with subject matter experts to interpret results accurately.

What to do in factor analysis?

Factor analysis is a statistical method used by data analysts and researchers to identify underlying variables or factors that explain the patterns in large datasets. The process involves selecting appropriate data, checking assumptions, extracting factors using techniques like principal component analysis, and interpreting the results to inform decision-making or further analysis. Proficiency with statistical software such as SPSS, R, or SAS is often required.

What is the difference between Factor Analysis vs Data Analyst?

AspectFactor AnalysisData Analyst
Primary RoleStatistical technique to identify underlying variablesInterpreting data to provide insights and support decision-making
Required SkillsStatistics, mathematics, data modelingData manipulation, visualization, statistical analysis
Work EnvironmentResearch, academia, data science projectsBusiness, finance, marketing, healthcare
Common CertificationsStatistics, data science certificationsData analysis, business intelligence certifications

Factor Analysis is a statistical method used to reduce data dimensions and identify latent variables, often used in research. Data Analysts interpret data to generate actionable insights across various industries. While Factor Analysis is a specialized technique within data analysis, Data Analysts perform broader tasks involving data collection, cleaning, and reporting.

What is the highest paying job in data analytics?

In data analytics, senior roles such as Data Science Manager, Director of Data Analytics, or Chief Data Officer typically have the highest salaries, often exceeding six figures annually. These positions require advanced skills in statistical analysis, machine learning, and leadership, along with experience in tools like Python, R, and SQL.

What exactly is factor analysis?

Factor analysis is a statistical method used to identify underlying variables, called factors, that explain the patterns of correlations among observed data. In a job context, professionals use it to reduce data complexity, interpret large datasets, and support decision-making, often utilizing software like SPSS or R. It requires strong analytical skills and understanding of statistical concepts.

What are the key skills and qualifications needed to thrive as a Factor Analyst, and why are they important?

To thrive as a Factor Analyst, you need a strong background in statistics, mathematics, and data analysis, typically supported by a degree in statistics, psychology, or a related field. Familiarity with statistical software such as SPSS, R, or SAS and an understanding of psychometric or quantitative research methods are essential. Attention to detail, problem-solving abilities, and effective communication are key soft skills for interpreting complex data and presenting findings clearly. These skills ensure accurate analysis, meaningful insights, and effective collaboration with research or business teams.
What cities are hiring for Factor Analysis jobs? Cities with the most Factor Analysis job openings:
What states have the most Factor Analysis jobs? States with the most job openings for Factor Analysis jobs include:
Infographic showing various Factor Analysis job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution.
Data Analyst I

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 2 days ago


Job description

POSITION SUMMARY:  In this role, you will support data analysis, data modeling, and data warehousing efforts that directly impact our business, business partners, and clients in claims, underwriting, and risk assessment strategies. Whether you’re a recent graduate or early in your career, this position offers a strong foundation in data science, data warehousing, and insurance analytics, with opportunities for growth and development.

DUTIES AND RESPONSIBILITIES:

  • Assist in building data warehouse, dashboards, and reporting tools for actuarial, claims, and underwriting teams.
  • Collaborate with business units to develop data-driven insights for loss prevention and reserve modeling.
  • Clean, organize, and merge structured data from internal and third-party sources.
  • Write queries and scripts using SQL and Python or R to extract and analyze data efficiently.
  • Ensure data integrity and accuracy in reports and data feeds used for compliance, audit, and strategic planning.
  • Analyze claims, policy, and exposure data to identify trends in injury types, loss costs, and claim durations.
  • Apply basic statistical techniques or predictive models to support pricing, claims triage, or fraud detection.
  • Strong SQL development skillset in Postgres or any RDBMS database, data warehouse experience, Python, or Java core programming as a plus

PREFERRED SKILLS (Not Required)

  • Knowledge of workers’ compensation insurance and claims workflows
  • Internship or project experience in insurance analytics, risk modeling, or predictive modeling.
  • Understanding of regulatory reporting and industry data sources (e.g., NCCI, ISO).

QUALIFICATIONS REQUIRED:

  • Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
  • 0–3 years of experience in data science, analytics, or insurance-related projects (academic or professional).
  • Familiarity with data tools such as SQL, Python, R, or SAS.
  • Familiarity with Data warehouse techniques and practices
  • Hands on any data warehouse product
  • Exposure to data visualization tools (e.g., Power BI, Tableau).
  • Strong attention to detail, curiosity, and willingness to learn industry-specific data concepts.
  • Ability to work independently and collaboratively with cross-functional teams.

Here are some of the benefits you can enjoy in this role:

  • Medical, Dental, Vision Insurance
  • Life and Disability Insurance
  • 401(k) plan
  • Paid time off
  • Paid holidays

Mental and Physical Requirements:

MENTAL AND PHYSICAL REQUIREMENTS

1. MENTAL EFFORT

a.       Reasoning development::

          Follow one- or two-step instructions; routine, repetitive task.

          Carry out detail but uninvolved written or verbal instructions; deal with a few concrete variables.

          Follow written, verbal, or diagrammatic instructions; several concrete variables.

 X       Solve practical problems; variety of variables with limited standardization; interpret instructions.

          Logical or scientific thinking to solve problems; several abstract and concrete variables.

          Wide range of intellectual and practical problems; comprehend most obscure concepts.

b.       Mathematical development:

          Simple additional and subtraction; copying figures, counting, and recording.

          Add, subtract, multiply, and divide whole numbers.

 X       Arithmetic calculations involving fractions, decimals, and percentages.

          Arithmetic, algebraic, and geometric calculations.

          Advanced mathematical and statistical techniques such as calculus, factor analysis, and probability determination.

 

          Highly complex mathematical and statistical techniques such as calculus, factor analysis, and probability determination; requires theoretical application.

c.       Language development:

          Ability to understand and follow verbal or demonstrated instructions; write identifying information; request supplies verbally or in writing.

          Ability to file, post, and mail materials; copy data from one record to another; interview to obtain basic information such as age, occupation, and number of children; guide people and provide basic direction.

          Ability to transcribe dictation; make appointments and process mail; write form letters or routine correspondence; interpret written work instructions; interview job applicants.

 X       Ability to compose original correspondence, follow technical manuals, and have increased contact with people.

          Ability to report, write, or edit articles for publication; prepare deeds, contracts or leases, prepare and deliver lectures; interview, counsel, or advise people; evaluate technical data.

2. PHYSICAL EFFORT

a.       Physical activity required to perform the job:

          Sedentary work: Exerting up to 10 pounds of force occasionally and/or a negligible amount of force frequently or constantly to lift, carry, push, pull, or otherwise move objects. Sedentary work involves sitting most of the time. Jobs are sedentary if walking and standing are required only occasionally and all other sedentary criteria are met.

 X       Light work:

a.    Exerting up to 20 pounds of force occasionally b.       Exerting up to 10 pounds frequently

c.    Exerting a negligible amount of force constantly to move objects

(If the use of arm and/or leg controls requires exertion of forces greater than that for Sedentary

Work and the worker sits most of the time, the job is rated for Light Work).

          Medium work:

a.    Exerting up to 50 pounds of force occasionally b.       Exerting up to 20 pounds of force frequently

c.    Exerting up to 10 pounds of force constantly to move objects

          Heavy work:

a.    Exerting up to 100 pounds of force occasionally b.       Exerting up to 50 pounds of force frequently

c.    Exerting up to 20 pounds of force constantly to move objects

 

          Very heavy work:

a.    Exerting in excess of 100 pounds of force occasionally

b.    Exerting in excess of 50 pounds of force constantly to move objects c.       Exerting in excess of 20 pounds of force constantly to move objects

b.       Visual requirements necessary to perform the job:

          Far vision: clarity of vision at 20 feet or more

 X       Near vision: clarity of vision at 20 inches or less

 X       Mid-range vision: clarity of vision at distances of more than 20 inches and less than 20 feet

          Depth perception: the ability to judge distance and space relationships, so as to see objects where and as they actually are

          Color vision: ability to identify and distinguish colors

          Field of vision: ability to observe an area up or down or to the right or left while eyes are fixed on a given point

2. PHYSICAL EFFORT (cont.)

FREQUENCY

c.    Physical activity necessary to perform the job and frequency (e.g., continually, frequently, or occasionally):

      Climbing:       Ascending or descending ladders, stairs, scaffolding, ramps, poles, and

the like, using feet and legs and/or hands and arms. Body agility is emphasized. This factor is important if the amount and kind of climbing required exceeds that required for ordinary locomotion.

      Balancing:       Maintaining body equilibrium to prevent falling when walking, standing, or crouching on narrow, slippery, or erratically moving surfaces. This factor is important if the amount and kind of balancing exceeds that needed for ordinary locomotion and maintenance of body equilibrium.

 X   Stooping:      Bending body downward and forward by bending spine at the waist.

This factor is important if it occurs to a considerable degree and requires full use of the lower extremities and back muscles.

 X  Kneeling:      Bending legs at knee to come to a rest on knee or knees.

 X   Crouching:    Bending the body downward and forward by bending legs and spine.

        Crawling:      Moving about on hands and knees or hands and feet.

 X   Reaching:      Extending hand(s) and arm(s) in any direction.

Occasionally

Occasionally

Occasionally Occasionally Occasionally

 

 X  Standing:        Particularly for sustained periods of time.

 X   Walking:       Moving about on foot to accomplish tasks, particularly for long distances.

 X   Pushing:        Using upper extremities top press against something with steady force in order to thrust forward, downward, or outward.

 X  Pulling:          Using upper extremities to extent force in order to drag, haul, or tug objects in a sustained motion.

        Foot

Motion:          Using feet to push pedals.

 X   Lifting:          Raising objects from a lower to a higher position or moving objects horizontally from position to position. This factor is important if it occurs to a considerable degree and requires substantial use of the upper extremities and back muscles.

 X   Fingering:      Picking, pinching, typing, or otherwise working with fingers rather than with the whole hand or arm as in handling.

 X   Grasping:      Applying pressure to an object with the fingers and palm.

 

Occasionally Occasionally Occasionally

Frequently

Frequently

Occasionally

2. PHYSICAL EFFORT (cont.)

FREQUENCY

 X  Talking:           Expressing or exchanging ideas by means of the spoken word. Those activities in which workers must convey detailed or important spoken instructions to other workers accurately, loudly, or quickly.

 X  Hearing:         Perceiving the nature of sounds with or without correction. Ability to receive detailed information through verbal communication, and to make fine discriminations in sound, such as when making find adjustments on machined parts.

      Feeling:           Perceiving attributes of objects, such as size, shape, temperature, or texture by touching with skin, particularly that of fingertips.

 X  Repetitive      Substantial movements (motions) of the wrists, hands, Motion:          and/or fingers.

Frequently

Frequently

Frequently

3. WORKING CONDITIONS

Disagreeable job conditions to which the employee may be exposed and the frequency (e.g., continually, frequently, or occasionally) of this exposure.

 

WORKING CONDITION ENVIRONMENTAL

FACTOR

NATURE/REASON OF EXPOSURE

FREQUENCY

Dirt/Dust

Noise

Temperature extremes

Dampness

Vibrations

Equipment movement hazard

Chemicals/solvents

Electrical shock

Significant work pace/pressure

Odors/Fumes

Other (specify):                             Â