Hi everyone! I'm reaching out for advice as a 2023 graduate on my resume. I want your honest opinions for someone looking to get into business or data analytics.

It feels like the freshest of freshies would get picked, or someone who was able to nail an internship got their foot in the door with a company. Everyone has their paths, I'm still trying to find my first stepping stone and would love to hear constructive advice!

Thank you for reading my post and resume.

Human perspective now: I don’t feel I get a good idea of how deep your knowledge in your skill section is. How proficient in python etc maybe give an insight into methods you are familiar with. Also a brief summary profile is nice where you can customize your cv a bit for each job. That is more of a general advice to really customize your cv to the job you are interested in and give more specific insights in those action items. You can do it!

I have asked ChatGPT to review your resume , do a deep research and come up with a plan, and also suggest changes to your resume to improve chances of getting that stepping stone job. The response is long so I will divide it in several sections. Good luck !
Section 1

Promising Entry-Level Roles in Analytics
• Business Analyst: Gathers and documents business requirements, analyzes processes, and helps implement solutions . This role leverages the candidate’s Business Analysis background and skills (Excel, Agile, ERP) to bridge business needs and IT.
• Business Systems Analyst: Focuses on requirements gathering and software implementation (especially ERP/CRM systems). Daily tasks include user interviews, process mapping, and testing new systems . With ERPNext experience and project management training, this is a natural fit.
• Data Analyst: Collects, cleans, and analyzes data to provide actionable insights . Responsibilities include statistical analysis, reporting, and data visualization (using SQL, Python/R, Tableau) . Strong programming skills and tools match the candidate’s R/Python/SQL expertise.
• Business Intelligence (BI) Analyst: Designs and maintains dashboards/reports and interprets data trends . BI Analysts “collect and analyse data to identify trends” and build data models and reports for decision-makers . Experience with Tableau and data storytelling would be key here.
• Operations/Reporting Analyst: Works on internal metrics and operational data, often optimizing processes. A stepping-stone role might involve maintaining daily/weekly reports, supporting finance or supply-chain analytics.
• ERP/Systems Analyst: Given the ERPNext experience, look for junior ERP Analyst or Systems Analyst roles. These focus on customizing and supporting business software (ERP, Salesforce, etc.), combining business know-how and technical skills.

Each of these entry-level titles emphasizes analytical tools and clear communication. For example, an Entry-Level Business Analyst “supports the collection and analysis of data…providing better solutions” , while an Entry-Level Business Systems Analyst “assists in gathering and documenting business requirements, analyzing workflows, and supporting the implementation of new software” . These duties align well with the candidate’s project experience in R/Tableau and their agile/project management certification.

Section 2

Target Industries and Companies

The Los Angeles market has demand for analytics roles across many sectors. Examples of local and remote-friendly employers include:
• Healthcare: Kaiser Permanente (and other hospitals or healthcare groups) routinely post data/analytics positions. For instance, Kaiser’s career site lists roles like “Data Reporting and Analytics Consultant III” (Pasadena, CA) . University medical centers and insurers (e.g. UCLA Health, Cedars-Sinai, Anthem) also hire early-career analysts.
• Finance & Insurance: Banks and financial firms in LA (e.g. East West Bank) use data analysts. LinkedIn shows East West Bank recruiting Data Analyst interns in Pasadena . Insurance companies (e.g. Farmers, AIG) and fintech startups are also hiring analytics or actuarial interns and analysts.
• Technology & Media: Major tech firms with LA presence (Snap Inc., Google, Amazon) and entertainment companies (Netflix, NBCUniversal, Disney, WarnerMedia) have analytics and BI teams. For example, NBCUniversal recently advertised a Senior BI Engineer role in LA (showing they invest in analytics). Snap’s careers site lists Business Intelligence Engineer roles based in Los Angeles . Remote-friendly tech companies (like Microsoft, Databricks, or remote-first startups on AngelList) can also be considered.
• Consulting & Professional Services: Firms like PwC, Deloitte, and KPMG have data analytics and finance analytics practices in LA or work remotely. For example, a PwC listing on BuiltInLA shows a Cloud Data & Analytics Senior Manager opening (hybrid LA/remote) . These companies often have rotational or analyst programs for new grads.
• Retail & eCommerce: Companies like Walmart Labs (Carlsbad/LA), Thrive Market (LA-based), Whatnot (e-commerce) and other consumer brands hire data/reporting analysts. BuiltInLA highlights roles at startups such as Whatnot and Centerfield in LA.
• Manufacturing/Defense: Local firms like The Aerospace Corporation and Northrop Grumman need data analysts for operations and R&D. (BuiltInLA shows Aerospace Corporation hiring for analytics/data engineering).
• Education & Public Sector: Universities (UCR, USC, UCLA) and government (City/County of LA, LADWP) have analyst positions. Check university career boards and government job portals for analyst or data roles.

Additionally, broad job platforms (LinkedIn, Indeed, Glassdoor, ZipRecruiter, BuiltInLA) consistently show dozens of entry-level analytics positions in the LA area and remote roles. For instance, Indeed lists 25+ entry-level data analyst jobs in Los Angeles , and LinkedIn shows over 30 data analytics internships (e.g. at Lensa, East West Bank, Ormco)

Section 3

Recommended Job Titles and Descriptions

Based on the candidate’s profile, target job titles such as:
• Business Analyst (entry/junior): “Supports data-driven decisions by generating reports and conducting detailed analysis” . Duties include stakeholder interviews, requirements documentation, process mapping, and recommending improvements .
• Business Systems Analyst: Focus on ERP or IT systems. Tasks: gather requirements, configure software (e.g. ERPNext), test new functionality, and train users .
• Data Analyst: Collect and clean datasets, run statistical analyses, and build visual dashboards . Emphasize SQL queries, Python/R scripting, and tools like Tableau in the job description.
• Business Intelligence Analyst: Emphasize advanced reporting: designing dashboards, performing data modeling, and presenting insights to management . Often requires knowledge of BI platforms (Tableau, PowerBI) and SQL.
• Reporting Analyst / Data Reporting Specialist: Focus on maintaining routine reports (sales, finance, operations) and improving their accuracy. Great for leveraging Excel and attention to detail.
• Operations Analyst: Involves analyzing supply chain, manufacturing, or logistic data to optimize workflows.
• ERP Analyst / Implementation Specialist: Use ERPNext and CompTIA/IT skills to help companies implement business software. Involves translating business needs into system configs and supporting end-users.

For each title, include keywords on the resume/application: e.g., “SQL”, “Python”, “R”, “Tableau”, “Excel”, “Agile”, “ERPNext”, “data modeling”, “dashboards”, “requirements gathering”. Use the job postings as a guide to align phrasing. For example, many “Entry-Level Business Analyst” postings note tasks like “conducting research and analysis, generating reports, and assisting with solution development” , so mirror that language.

Section 4

Step-by-Step Job Search Strategy
1. Optimize Your Resume & LinkedIn: Tailor your resume for each role. Highlight your SQL/Python/R and Tableau experience (from coursework/projects). Include any academic projects or internships that “apply analytical techniques to solve problems” . Use strong action verbs (e.g. Analyzed, Assessed, Improved) to describe achievements . Quantify results when possible (e.g. “improved report accuracy by 30%”, “processed 10,000+ records”). List your technical skills prominently (Python, R, SQL, Tableau, Excel, ERPNext, etc.) as suggested by career experts . A concise, reverse-chronological format with clear section headers will help hiring managers scan quickly. Ensure consistency (fonts, bullet style) and proofread carefully.
2. Use Job Platforms & Company Sites: Search broadly on LinkedIn, Indeed, Glassdoor, ZipRecruiter and niche sites (BuiltInLA for startups, Handshake for university alumni, AngelList for startups). Set alerts for “entry level data analyst” or “business analyst”, etc. Use filters for Los Angeles or remote, and include internships/contract roles. For example, Indeed’s LA search shows many entry-level data analyst openings . Also visit target companies’ careers pages (e.g. Snap, Kaiser, Northrop, etc.) to apply directly. Don’t overlook contract or apprenticeship postings.
3. Network Actively: Engage your alumni network (UCR and Pierce College alumni groups), and reach out to UC Riverside career center or mentors for referrals. Use LinkedIn to connect with professionals in analytics roles at your target companies (send polite messages asking for advice or informational interviews). Join relevant Meetup or Slack groups. For instance, the Los Angeles Data Science / Machine Learning Meetup has ~1,900 members and explicitly serves beginners in the field . Attend local events or virtual webinars in analytics, data science, and business analysis to meet recruiters and peers.
4. Showcase Projects & Learning: Build a small portfolio (e.g. a GitHub or personal site) with sample analyses or dashboards. You might redo an open dataset analysis in R or Python and share interactive Tableau visuals. Completing online challenges (Kaggle, StrataScratch) or projects in your resume (as per ) demonstrates initiative. Also, leverage your certifications (CompTIA ITF+, Google IT, Agile). Platforms like Coursera or LinkedIn Learning offer capstone projects you can mention.
5. Apply Strategically and Follow Up: Apply to multiple roles daily and keep a tracking spreadsheet. Tailor each cover note/resume to the job description. For remote roles, emphasize your self-starter traits (you have remote experience). After applying, follow up with short emails or LinkedIn messages to recruiters when possible. Prepare for interviews by reviewing common analytics case questions and practicing explaining your projects clearly.

Throughout, emphasize your strong analytical toolkit and teamwork skills. For example, in networking conversations and interviews, note your remote co-founder experience as leadership/coordination (“coordinated a remote team to launch a startup project”), and frame your data entry role as a demonstration of accuracy and diligence. Use the STAR method (Situation-Task-Action-Result) to describe experiences in interviews.

Section 5 (and final)

Resume and Profile Enhancements
• Highlight Skills & Projects: As an entry candidate, “focus on relevant coursework, academic projects, or internships” that used analytical tools . List Python, R, SQL, Tableau (and ERPNext) in a Technical Skills section . For each project or job bullet, start with a strong verb (e.g. Analyzed, Cleaned, Automated) and quantify outcomes if possible.
• Detail Achievements: Convert your duties into achievements. Instead of “Entered data into CRM”, say “Maintained 99% accuracy entering 5,000+ customer records into CRM, reducing errors by 30%” (tailored to actual figures). Show how your work impacted the team or project. If you implemented something (even in coursework), highlight the benefit: “Developed a Tableau dashboard to track sales trends, improving decision speed by 20%.” This aligns with advice to use action verbs and metrics .
• Bullet Clarity: Keep each bullet 1–2 lines max. Use parallel structure (all starting with past-tense verbs). Ensure there are no large text blocks – readers should scan quickly. The ResumeWorded examples emphasize strong verbs and conciseness .
• Education & Certifications: List your B.S. and associate degrees, but lead with your university and major (Business Admin, emphasis Business Analysis). Include key coursework (e.g. “Business Analytics” or “Data Management”) if space. Mention certifications (CompTIA ITF+, Google IT Support, Agile) under Education or Certifications. These validate your tech knowledge.
• LinkedIn Profile: Make sure LinkedIn matches your resume. Use a professional photo and headline like “Business/ Data Analyst | SQL, Python, Tableau”. In the summary, briefly state your goals (“Recent BA grad specializing in data analysis seeking entry-level Analyst role”) and highlight your key skills and certifications. Ask connections for recommendations or endorsements in SQL/Python/Tableau to boost credibility.

By clearly showcasing quantifiable achievements, relevant projects, and polished technical skills, your resume will stand out. As a guideline, top entry-level resumes list projects and skills prominently .

Resources: For searches, use job boards (Indeed , LinkedIn , BuiltInLA, etc.) and company career pages. Networking groups like the [LA Data Science Meetup] (Meetup) are valuable . For resume tips, sites like ResumeWorded recommend emphasizing technical projects and action verbs . Armed with a targeted list of roles, a strong resume, and proactive networking, you’ll improve your chances in landing that entry-level analytics position.

Sources: Industry role descriptions and tips , job boards/companies (Indeed, LinkedIn, Kaiser, Snap, NBCUniversal) , and career advice (resume tips)