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Entry Level Data Analysis Jobs in Missouri (NOW HIRING)

Develop and review stress reports, technical documentation, and certification data * Collaborate ... Experience in structural or stress analysis (typically 2+ years for entry-level roles) * Knowledge ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Industry/Sector Not Applicable Specialism Data, Analytics & AI Management Level Senior Associate ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

... data analysis, forecasting, job costing, pricing, etc. These tasks will be performed in support of ... This is an entry level position. Responsibilities Your core responsibilities include: * Provide ...

... data analysis, forecasting, job costing, pricing, etc. These tasks will be performed in support of ... This is an entry level position. Responsibilities Your core responsibilities include: * Provide ...

... data analysis, forecasting, job costing, pricing, etc. These tasks will be performed in support of ... This is an entry level position. Your core responsibilities include: * Provide reporting to support ...

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Entry Level Data Analysis information

See Missouri salary details

$12

$30

$57

How much do entry level data analysis jobs pay per hour?

As of Jun 29, 2026, the average hourly pay for entry level data analysis in Missouri is $30.89, according to ZipRecruiter salary data. Most workers in this role earn between $19.86 and $34.52 per hour, depending on experience, location, and employer.

What are some common challenges entry-level data analysts face when starting out, and how can they overcome them?

Entry-level data analysts often encounter challenges such as learning new data tools, understanding unfamiliar datasets, and translating business questions into analytical tasks. It's common to feel overwhelmed by the variety of software (like Excel, SQL, or Python) and the pace of real-world projects. To overcome these hurdles, new analysts should proactively seek mentorship, participate in team discussions, and take advantage of online resources or internal training. Regular collaboration with colleagues and asking clarifying questions can help build confidence and ensure successful project contributions.

How to get hired as an entry-level data analyst?

To get hired as an entry-level data analyst, candidates should develop foundational skills in data analysis tools like Excel, SQL, and Python or R, and build a portfolio of relevant projects. Earning certifications such as Microsoft Data Analyst Associate or Google Data Analytics can improve prospects, along with gaining internship experience or completing relevant coursework. Strong communication skills and the ability to interpret data for non-technical audiences are also important.

Can I be a data analyst with no experience?

Entry level data analyst positions often do not require prior professional experience, but having skills in Excel, SQL, or data visualization tools can improve your chances. Many employers value relevant coursework, certifications, or internships that demonstrate your ability to analyze data effectively.

What is an entry level data analyst?

An entry level data analyst is a professional who collects, processes, and performs basic analysis on data to help organizations make informed decisions. They typically work with tools like Excel, SQL, or data visualization software to organize and interpret data sets. Entry level analysts focus on tasks such as cleaning data, creating reports, and identifying trends, usually under the supervision of more experienced analysts. This role is ideal for recent graduates or individuals starting their career in data analysis.

Is 40 too late for data science?

Entry level data analysis roles are accessible at any age, including at 40 or older. Success depends on acquiring relevant skills such as proficiency in Excel, SQL, and data visualization tools, as well as building a strong portfolio and gaining practical experience. Age is less important than skills, continuous learning, and adapting to industry tools and methods.

What are the key skills and qualifications needed to thrive as an Entry Level Data Analyst, and why are they important?

To thrive as an Entry Level Data Analyst, you need foundational knowledge in statistics, data interpretation, and a relevant degree such as in mathematics, economics, or computer science. Familiarity with tools like Microsoft Excel, SQL, and data visualization platforms such as Tableau or Power BI is typically required. Strong analytical thinking, problem-solving abilities, and clear communication help you extract meaningful insights and present findings effectively. These skills are crucial for transforming raw data into actionable information that supports informed business decisions.

Is AI replacing data analysts?

AI tools are automating certain repetitive tasks in data analysis, such as data cleaning and basic reporting, but they do not replace the need for skilled data analysts. Entry-level data analysis roles still require critical thinking, domain knowledge, and interpretation skills that AI cannot fully replicate. Professionals who develop expertise in data visualization, programming, and statistical methods remain valuable in the field.

What is the difference between Entry Level Data Analysis vs Data Analyst?

AspectEntry Level Data AnalysisData Analyst
Required CredentialsAssociate's degree or relevant certificationBachelor's degree often preferred
Work EnvironmentInternships, entry-level roles, training programsFull-time positions in various industries
Employer & Industry UsageStart of career, learning phaseMid-level roles, more responsibilities
Common Search & Comparison IntentUnderstanding entry-level opportunitiesAdvancement and skill development

Entry Level Data Analysis roles are designed for beginners with minimal experience, focusing on learning foundational skills. Data Analysts typically have more experience, handle complex data projects, and contribute to strategic decision-making. The main difference lies in experience level, responsibilities, and career progression.

What are the most commonly searched types of Data Analysis jobs in Missouri? The most popular types of Data Analysis jobs in Missouri are:
What job categories do people searching Entry Level Data Analysis jobs in Missouri look for? The top searched job categories for Entry Level Data Analysis jobs in Missouri are:
What cities in Missouri are hiring for Entry Level Data Analysis jobs? Cities in Missouri with the most Entry Level Data Analysis job openings:
Infographic showing various Entry Level Data Analysis job openings in Missouri as of June 2026, with employment types broken down into 74% Full Time, 20% Part Time, 1% Temporary, and 5% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $64,241 per year, or $30.9 per hour.
AML and Sanctions- Data Scientist- Senior Associate

AML and Sanctions- Data Scientist- Senior Associate

Pwc

Kansas City, MO

$77K - $202K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 6 days ago


PwC rating

8.3

Company rating: 8.3 out of 10

Based on 75 frontline employees who took The Breakroom Quiz

20th of 57 rated business consultants


Job description

Industry/Sector

Banking and Capital Markets

Specialism

Data, Analytics & AI

Management Level

Senior Associate

Job Description & Summary

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.
In business intelligence at PwC, you will focus on leveraging data and analytics to provide strategic insights and drive informed decision-making for clients. You will develop and implement innovative solutions to optimise business performance and enhance competitive advantage.
Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn't clear, you ask questions, and you use these moments as opportunities to grow.
Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:
Respond effectively to the diverse perspectives, needs, and feelings of others.
Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
Use critical thinking to break down complex concepts.
Understand the broader objectives of your project or role and how your work fits into the overall strategy.
Develop a deeper understanding of the business context and how it is changing.
Use reflection to develop self awareness, enhance strengths and address development areas.
Interpret data to inform insights and recommendations.
Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
The Opportunity
As part of the Financial Crime Unit team you will apply analytical methods to complex datasets leveraging SQL and Python. As a Senior Associate you will analyze intricate problems, mentor Associates, and maintain exemplary standards while building meaningful client relationships. This role offers the chance to deepen your technical knowledge and personal brand while navigating the complexities of financial crime detection and machine learning applications.
Responsibilities
- Apply machine learning and natural language processing to financial crime challenges
- Develop a thorough understanding of the business landscape
- Navigate intricate scenarios to enhance personal and technical growth
- Leverage SQL and Python for data analysis and problem-solving
What You Must Have
- Bachelor's Degree in Computer and Information Science, Economics, Engineering, Operations Management/Research, Statistics, Data Processing/Analytics/Science, Mathematics
- 3 years of professional experience in data science/machine learning
What Sets You Apart
- Experience mentoring junior team members
- Proven ability in developing machine learning models
- Demonstrating advanced skills in Python and SQL
- Familiarity with MLOps practices for model monitoring
- Comfort working with structured and unstructured data
- Experience with cloud platforms and containerization
- Knowledge of agentic AI frameworks for workflows
- Ability to translate client requirements into analytical solutions
- Proficiency in SQL and Python
- Hands-on experience with ML frameworks (scikit-learn, XGBoost, LightGBM, Hugging Face)
- Thorough understanding of model evaluation metrics across tasks

Travel Requirements

Up to 60%

Job Posting End Date

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glanceAs PwC is anequal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy: https://pwc.to/H-1B-Lottery-Policy.Learn more about how we work: https://pwc.to/how-we-workFor only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.

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