# 60-Day Job Search Plan: Junior Data Analyst — Lagos, Nigeria ## 1. Career Snapshot **Current position:** Recent Economics graduate transitioning into data analytics. **Primary objective:** Secure an entry-level **Junior Data Analyst / Data Analyst** opportunity in Lagos within 60 days, with openness to onsite or hybrid work. ### Strongest qualifications * Economics degree — useful foundation for quantitative reasoning, business analysis, markets, and interpreting trends. * Excel training — directly relevant to data cleaning, analysis, formulas, pivot tables, and reporting. * SQL training — important for querying and extracting data from databases. * Power BI training — relevant for dashboards, reporting, and business intelligence. * Basic Python — useful as a supporting analytical skill. * Two personal data-analysis projects — particularly valuable because they provide evidence of practical ability despite having no formal experience. ### Your positioning Rather than presenting yourself simply as **"a graduate with no experience,"** position yourself as: > **An Economics graduate with practical training in Excel, SQL, Power BI, and Python who has applied these skills to personal data-analysis projects and is seeking an entry-level opportunity to contribute to data-driven decision-making.** Your biggest challenge is not necessarily the absence of employment history. It is **proving that you can perform practical analyst tasks in a professional environment.** --- # 2. Target Role Strategy Don't restrict the search to one title. Employers use different titles for similar entry-level responsibilities. ### Realistic targets | Target role | Fit | Why | | ------------------------------------------ | --------------- | -------------------------------------------------------- | | **Junior Data Analyst** | Strong | Direct match with your current skills | | **Entry-Level Data Analyst** | Strong | Suitable for a recent graduate with projects | | **Reporting Analyst** | Strong | Excel, SQL and Power BI are highly relevant | | **Business Intelligence Analyst — Junior** | Moderate–Strong | Power BI and SQL provide a useful foundation | | **Data/Business Analyst Intern** | Strong | Good route for gaining professional experience | | **Data Analyst Intern** | Strong | Particularly appropriate if employers require experience | | **MIS/Reporting Officer** | Moderate–Strong | Reporting and Excel skills can transfer well | | **Operations/Data Analyst** | Moderate–Strong | Economics + analytics can be relevant | | **Business Analyst — Entry Level** | Moderate | Possible, but requirements vary significantly | | **Research/Data Assistant** | Moderate | Economics background can be useful | ### Stretch opportunities Consider roles such as: * BI Analyst * Product Analyst * Financial/Data Analyst * Marketing Data Analyst * Risk/Data Analyst These should be evaluated based on the **actual job description**, rather than applying simply because "Analyst" appears in the title. ### Roles requiring more preparation Be cautious about positions that expect: * Advanced Python * Machine learning * Advanced statistics * Several years of professional experience * Advanced cloud/data engineering * Complex ETL/data engineering * Senior-level Power BI development Don't spend your 60 days trying to become a data scientist. Your immediate objective is to become **employable for entry-level analytics work.** --- # 3. Skills & Qualification Gap Analysis ## Current strengths ### 1. Economics Your Economics degree can support work involving: * Business trends * Financial data * Market analysis * Economic indicators * Forecasting concepts * Quantitative reasoning * Interpretation of business results ### 2. Excel Make sure you can demonstrate more than basic spreadsheet knowledge. Prioritize: * XLOOKUP * INDEX/MATCH * IF/IFS * SUMIFS/COUNTIFS * PivotTables * Charts * Conditional formatting * Data cleaning * Basic dashboards * Power Query ### 3. SQL You should be comfortable with: ```text SELECT WHERE ORDER BY GROUP BY HAVING JOIN CASE WHEN COUNT SUM AVG MIN/MAX Subqueries CTEs Window functions ``` You don't need to master every advanced SQL feature before applying. ### 4. Power BI Prioritize: * Data import * Data cleaning with Power Query * Relationships * Basic data modeling * DAX fundamentals * Measures * Interactive dashboards * Filters/slicers * Business-oriented visualizations ### 5. Python Treat Python as a supporting skill rather than the center of your job-search strategy. Focus on: * pandas * NumPy basics * Data cleaning * Data exploration * Basic visualization * Reading CSV/Excel files --- ## Priority gaps ### High priority **Professional portfolio** Your two projects need to look like analyst projects rather than school exercises. Each project should clearly show: 1. Business/problem question 2. Dataset 3. Data cleaning 4. Analysis 5. Key findings 6. Visualizations/dashboard 7. Recommendations 8. Tools used ### High priority **SQL practice** You should be able to complete practical SQL questions without depending heavily on tutorials. ### High priority **Interview communication** You need to explain: > "What did you do?" not simply: > "I know SQL." ### Medium priority **Power BI/DAX** Strengthen your ability to build a dashboard from raw data. ### Medium priority **Professional networking** You currently need relationships that can expose you to opportunities and provide insight into what employers actually expect. --- # 4. Job Search Channels Use several channels rather than relying on one website. ### Job boards Search Nigerian and international job platforms for: * Junior Data Analyst * Data Analyst Intern * Reporting Analyst * Business Intelligence Analyst * Business Analyst * MIS Analyst * Research/Data Analyst Examples include **LinkedIn Jobs, Jobberman, Indeed, MyJobMag**, and relevant Nigerian graduate/technology job communities. ### Company career pages Create a list of Lagos-based employers in areas such as: * Banking * Fintech * Telecommunications * Consulting * E-commerce * FMCG * Logistics * Insurance * Healthcare * Technology * Market research * Professional services Don't wait for every opportunity to appear on a job board. Check the careers pages of companies you would genuinely consider. ### LinkedIn Your LinkedIn profile should communicate your target clearly. **Headline example:** > Economics Graduate | Junior Data Analyst | Excel | SQL | Power BI | Python | Data Analytics Your **Featured** section should showcase your two strongest projects. --- # 5. Application Strategy Your goal should **not** be 500 random applications. For this 60-day search, target approximately: ### **8–12 quality applications per week** Over eight weeks: **64–96 targeted applications** The number can increase if suitable vacancies are abundant, but quality should remain the priority. ## Before applying For each vacancy, ask: ### A. Do I meet the core requirements? Look for genuine alignment in: * Excel * SQL * Power BI * Data analysis * Reporting * Business analysis * Education ### B. Is the experience requirement realistic? Don't automatically reject yourself because a posting says "1–2 years experience" if the responsibilities are genuinely entry-level and your projects demonstrate relevant ability. However, don't spend substantial time on roles demanding several years of specialized professional experience. ### C. Can I demonstrate the required skill? If the job asks for Power BI, your portfolio should ideally contain a Power BI project. --- ## Application workflow **Find → Evaluate → Customize → Apply → Track → Follow up → Prepare** Maintain one spreadsheet containing every application. For particularly relevant jobs, customize: * Resume keywords * Professional summary * Relevant project descriptions * Cover letter, when requested --- # 6. Weekly Job Search Plan ## Week 1 — Build your foundation **Applications:** 5–8 Tasks: * Finalize your target job titles. * Create/update your ATS-friendly resume. * Update LinkedIn. * Review your two existing projects. * Create a professional portfolio location. * Identify 30–40 companies to monitor. * Begin daily SQL practice. * Start your application tracker. **Networking:** Contact 5 people. **Interview:** Prepare your 60-second introduction. --- ## Week 2 — Strengthen your portfolio **Applications:** 8–10 Improve Project #1. Your project should answer: > What business problem did I solve and what did the data tell me? Add: * Dataset explanation * Cleaning process * Analysis * Visualizations * Findings * Recommendations **Networking:** 5–8 conversations. **Technical practice:** SQL + Excel. --- ## Week 3 — Build stronger evidence **Applications:** 8–12 Improve Project #2. Preferably make the two projects different. For example: **Project 1:** Sales/customer analysis **Project 2:** Economics/financial/market analysis This allows you to demonstrate both technical and domain knowledge. **Interview:** Practice explaining both projects aloud. --- ## Week 4 — Increase market exposure **Applications:** 10–12 Start targeting: * Banks * Fintech companies * Consulting firms * Telecommunications * FMCG * Logistics * Technology companies * Research organizations **Networking:** 8–10 meaningful conversations. **Technical:** Complete timed SQL exercises. --- ## Week 5 — Interview readiness **Applications:** 8–12 Focus heavily on interview preparation. Practice: * SQL questions * Excel questions * Power BI questions * Behavioral questions * Project questions * Economics/business questions Conduct at least **2 mock interviews**. --- ## Week 6 — Refine based on feedback **Applications:** 8–12 Look at your results. If you have many applications but no interviews, investigate: * Resume positioning * Job targeting * Keywords * Portfolio quality * Experience alignment If you're getting interviews but not progressing, focus more heavily on: * Communication * Technical testing * Project explanations * Behavioral answers --- ## Week 7 — Target high-value opportunities **Applications:** 8–12 Prioritize employers where your background has a logical connection. For example: **Economics + Data Analytics →** * Banking * Financial services * Fintech * Research * Consulting * Business intelligence * Market analysis Continue networking and interview preparation. --- ## Week 8 — Final 60-day push **Applications:** 8–12 Review every active application. Follow up where appropriate. Continue interviewing. Update your portfolio based on questions you've encountered. Create a list of: * Applications still active * Interviews completed * Skills employers repeatedly request * Networking contacts * Companies to continue targeting after Day 60 The end of 60 days should not mean the end of the search. It should produce a **better candidate with a stronger network, portfolio, resume, and interview ability.** --- # 7. Job Application Tracker | Company | Position | Date Applied | Status | Contact Person | Follow-Up Date | Interview Date | Next Action | Notes | | --------- | ------------------- | ------------ | --------- | -------------- | -------------- | -------------- | ----------------- | ----- | | Company A | Junior Data Analyst | | Applied | | | | Follow up | | | Company B | Data Analyst Intern | | Applied | | | | | | | Company C | Reporting Analyst | | Applied | | | | | | | Company D | Business Analyst | | Screening | | | | Prepare interview | | Add a **Job Fit** column if possible: * Strong fit * Reasonable fit * Stretch This will prevent you from treating every vacancy equally. --- # 8. Networking Strategy Your objective isn't to ask strangers: > "Please give me a job." Instead, build professional relationships. ## Who to connect with Look for: * Data Analysts * Senior Data Analysts * BI Analysts * Analytics Managers * Business Analysts * Recruiters * HR professionals * Economics graduates working in analytics * Nigerian technology professionals ## Conversation starter Hello [Name], I’m an Economics graduate currently building my career in data analytics, with practical training in Excel, SQL, Power BI, and Python. I came across your profile and noticed your experience in analytics. I’d be glad to connect and learn from your professional journey. After they respond, don't immediately ask for a job. Ask something useful: > "What technical skill would you recommend an entry-level analyst focus on to become more employable?" Or: > "When reviewing junior analyst candidates, what tends to distinguish someone who is actually ready to contribute?" These questions can generate valuable information. ### Follow-up After receiving advice: > "Thank you. I've started working on that area based on your recommendation. I appreciate the guidance." Then maintain the relationship naturally. --- # 9. Interview Preparation Prepare for four major categories. ## A. Technical questions ### Excel Practice: * How would you clean a dataset? * How do PivotTables work? * When would you use XLOOKUP? * How would you identify duplicates? * How would you analyze monthly sales? ### SQL Practice: * Find duplicate records. * Calculate totals by category. * Use JOINs. * Find the highest-value customers. * Calculate monthly revenue. * Use GROUP BY. * Use CASE statements. * Compare periods. ### Power BI Practice: * How do you import data? * What is Power Query? * What is a relationship? * What is a measure? * What is DAX? * How would you design a dashboard for management? --- ## B. Project questions Expect: > Tell me about your project. Prepare a concise structure: **Problem → Data → Process → Analysis → Finding → Recommendation** For example: > "The purpose of the project was to understand ____. I used ____ data and cleaned it using ____. I analyzed the data using ____. The analysis showed ____. Based on the findings, I recommended ____." Only use findings that actually came from your project. --- ## C. Behavioral questions Prepare answers for: * Tell me about yourself. * Why data analytics? * Why should we hire you? * Tell me about a difficult problem you solved. * Tell me about a mistake you made. * How do you handle learning a new tool? * Why should an Economics graduate work in data analytics? * Where do you want to develop professionally? --- ## D. Evidence bank Create a document containing **5–7 real examples** from: * University projects * Personal data projects * Coursework * Group assignments * Leadership activities * Volunteer activities * Independent learning For each example record: **Situation → Task → Action → Result → Lesson** Do not manufacture results or achievements. --- # 10. Progress Metrics Track progress every Sunday. | Metric | Weekly Target | | ----------------------------- | ------------: | | Quality applications | 8–12 | | Networking conversations | 5–10 | | Follow-ups | 3–8 | | SQL practice sessions | 3 | | Excel/Power BI practice | 2–3 | | Portfolio improvements | 1 | | Mock interview | 1 | | New professional connections | 5–10 | | Relevant job/company research | 10–15 | ### Track outcomes, not just activity Also record: * Applications → interviews * Interviews → next stages * Technical tests completed * Recruiter responses * Referrals * Portfolio views/messages * Skills repeatedly requested by employers If applications consistently produce no interviews, **change the strategy rather than simply increasing application volume.** --- # 11. Next 7 Days ### Day 1 — Define your market Create your target list: **Primary** * Junior Data Analyst * Data Analyst * Data Analyst Intern * Reporting Analyst **Secondary** * BI Analyst * MIS/Reporting Analyst * Business Analyst * Operations/Data Analyst --- ### Day 2 — Fix your resume Create a one-page ATS-friendly resume. Put emphasis on: **Economics degree → technical skills → data projects → analytical capabilities** Do not compensate for limited work experience by inventing achievements. --- ### Day 3 — Improve LinkedIn Update: * Headline * About section * Skills * Education * Projects * Featured section Make your target role obvious within seconds. --- ### Day 4 — Upgrade Project #1 Turn the first project into a professional case study. Include: **Problem → Dataset → Cleaning → Analysis → Dashboard/Visuals → Insights → Recommendations** --- ### Day 5 — SQL + Excel Spend approximately: **1 hour SQL** **1 hour Excel** Practice using realistic business datasets rather than only watching tutorials. --- ### Day 6 — Begin networking Send **5–10 personalized connection requests** to Nigerian analysts, recruiters, and professionals working in relevant companies. Focus on starting conversations rather than asking for employment immediately. --- ### Day 7 — First application session Find **5–8 genuinely relevant vacancies**. For each: 1. Read the entire description. 2. Compare requirements with your skills. 3. Determine your fit. 4. Customize your resume where appropriate. 5. Apply. 6. Record it in your tracker. 7. Set a follow-up date. Then review your first week and identify the biggest weakness to address in Week 2. --- ## Your 60-Day Focus The strategy can be summarized as: **Economics degree + Excel + SQL + Power BI + Python + 2 strong projects + targeted applications + networking + interview practice** Your immediate goal isn't to become an expert in every data technology. It is to demonstrate that you can **take a messy business question or dataset, analyze it with the tools you know, communicate what you discovered, and provide useful evidence-based insights.** That is the story your **resume, LinkedIn profile, portfolio, applications, and interviews** should consistently communicate.