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Overview

Mastering search strategies on JobLeap helps you discover the right opportunities faster. By combining natural language queries with strategic refinement, you can efficiently navigate the job market and uncover positions that perfectly match your needs.

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Core Search Principles

Be Specific Yet Flexible

Start with detailed queries, then adjust based on results

Leverage Natural Language

Ask complete questions with context and preferences

Iterate Strategically

Use follow-ups to refine rather than starting over

Explore Related Opportunities

Discover adjacent roles and alternative paths

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Be Specific Yet Flexible

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Start with Detail

Begin your search with a comprehensive query that includes your core requirements: 
"Senior full-stack engineer with React and Node.js in Austin, remote options preferred"

"Entry-level data analyst positions requiring Python and SQL, salary above $60,000"

"Machine learning engineer roles at Series A startups, experience with PyTorch"

"Product manager jobs in healthcare tech, 3-5 years experience"
Why specificity helps:
  • AI understands your true requirements
  • Results are immediately more relevant
  • Less time filtering through mismatches
  • Better initial salary and location targeting

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Adjust Through Follow-ups

Once you see initial results, refine strategically:
1

Review Initial Results

Scan the first 10-15 job cards to understand what’s available
2

Identify Patterns

Notice common requirements, salary ranges, or company types
3

Refine One Dimension

Adjust location, salary, skills, or experience level
4

Evaluate Changes

See how results shift with each refinement
5

Continue Iterating

Narrow or broaden until you find the sweet spot

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Finding the Right Balance

Add constraints:
  • Specify experience level more precisely
  • Include salary expectations
  • Add required technical skills
  • Narrow geographic area
  • Specify company size or type
Example:
  • Initial: “Software engineer jobs” (10,000+ results)
  • Refined: “Senior software engineer with Python and AWS, remote, $130k+” (45 results)
Remove constraints:
  • Broaden location (add “remote” or nearby cities)
  • Lower salary floor slightly
  • Reduce required skills to must-haves only
  • Expand experience range
  • Consider similar job titles
Example:
  • Initial: “Senior ML engineer with PhD, PyTorch and JAX, in Boulder, $200k+” (2 results)
  • Broadened: “ML engineer with PyTorch, remote or Colorado, $150k+” (28 results)
Optimal result count:
  • Enough variety to compare options
  • Not overwhelming to review
  • Can realistically apply to many
  • Allows quality over quantity
What to do:
  • Review all results thoroughly
  • Save interesting positions
  • Ask comparative questions
  • Research top companies

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Leverage Natural Language

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Ask Complete Questions

JobLeap understands context, so provide it:
  • Include Context
  • Specify Must-Haves
  • Mention Nice-to-Haves
  • State Dealbreakers
Better:
  • “I’m a bootcamp grad looking for my first data analyst role. What entry-level positions don’t require a degree?”
  • “I have 5 years in backend Java development. Show me senior roles using modern frameworks like Spring Boot”
  • “Career changer from teaching to UX design. Find junior positions that value transferable skills”
Why it works:
  • AI understands your background
  • Filters out mismatched requirements
  • Surfaces roles open to your situation

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Use Conversational Phrasing

"What companies are hiring React developers in Seattle right now?"

"Show me the highest-paying remote data science jobs"

"Which ML engineer positions don't require a PhD?"

"Find startups in fintech that are hiring product managers"

"What entry-level roles can I get with just Python and SQL?"
You don’t need to use keywords or rigid syntax. JobLeap understands conversational English just like talking to a career advisor.

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Strategic Search Techniques

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Progressive Refinement

Layer filters one at a time to maintain control:
1

Start Broad

“Data science jobs in the Northeast”Results: 300+ positions
2

Add Experience Level

“Show me mid-level and senior roles”Results: 180 positions
3

Specify Skills

“Which ones focus on Python and machine learning?”Results: 85 positions
4

Filter by Company Type

“Narrow to startups and mid-size companies”Results: 40 positions
5

Add Salary Floor

“Only show positions paying $130k or more”Results: 22 positions - perfect for review

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Comparative Searching

Use comparisons to make informed decisions:
Questions to ask:
  • “Compare software engineer opportunities: SF vs. NYC vs. Seattle”
  • “How do remote salaries compare to Austin on-site positions?”
  • “Which city has more machine learning jobs: Boston or Denver?”
What you learn:
  • Market size differences
  • Compensation variations
  • Cost of living adjusted value
  • Remote vs. local trade-offs
Questions to ask:
  • “What’s the difference between data analyst and data scientist roles?”
  • “Compare responsibilities: ML engineer vs. research scientist”
  • “How do product manager and product owner positions differ?”
What you learn:
  • Day-to-day work differences
  • Career trajectory implications
  • Skill requirement variations
  • Compensation differences
Questions to ask:
  • “Compare working at a startup vs. FAANG company”
  • “What’s the difference between Series A and Series C startups?”
  • “How do benefits differ between tech companies and consulting firms?”
What you learn:
  • Growth potential
  • Stability vs. upside
  • Culture differences
  • Compensation structure
Questions to ask:
  • “Do React jobs pay more than Vue.js positions?”
  • “Compare demand for Python vs. Java backend roles”
  • “Which pays better: AWS or Google Cloud expertise?”
What you learn:
  • Market demand
  • Salary premiums
  • Future-proofing decisions
  • Learning priorities

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Exploratory Searches

Discover opportunities you might not have considered: 
"What roles are similar to data analyst but pay more?"

"Show me adjacent career paths for frontend developers"

"What other positions use machine learning skills?"

"If I'm a project manager, what tech PM roles exist?"

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Boolean-Style Searching

While natural language works best, you can still be precise:
  • AND Logic
  • OR Logic
  • NOT Logic
Combine requirements:
  • “Python AND Django AND Docker”
  • “Remote AND equity AND health insurance”
  • “Startup AND Series B AND San Francisco”
Better natural phrasing:
  • “Roles requiring Python, Django, and Docker”
  • “Remote positions with equity and health benefits”
  • “Series B startups in San Francisco”

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Advanced Search Patterns

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The Funnel Approach

Start extremely broad, then systematically narrow:
1

Industry-Wide Search

“All software engineering jobs”Understand overall market
2

Technology Focus

“Software engineering with cloud technologies”See cloud-specific demand
3

Specific Stack

“Cloud engineer roles using AWS and Terraform”Target your exact skills
4

Geographic Filter

“In the Pacific Northwest or remote”Add location preferences
5

Company Culture

“At companies with strong work-life balance”Align with values
6

Final Criteria

“Salary above $140k, equity offered”Achieve your target list
Run multiple focused searches simultaneously:

Primary Target

“Senior full-stack engineer, React/Node.js, remote, $150k+”Your ideal role

Slight Stretch

“Lead engineer or tech lead positions, remote, $180k+”Growth opportunity

Broader Backup

“Mid-senior full-stack roles, any modern stack, hybrid OK, $130k+”Safety net

Different Direction

“Engineering manager positions, remote, previous IC experience valued”Career pivot

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The Deep Dive

Focus on one company or role type extensively: 
"All engineering positions at [Company Name]"

"What's the culture like at [Company Name]?"

"Show me [Company Name]'s salary ranges for engineers"

"Tell me about career growth at [Company Name]"

"Compare [Company Name] to similar companies"

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Search Strategy by Goal

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Active Job Seeking

Goal: Find and apply to 10-20 relevant positionsStrategy:
  1. Start with 3-4 parallel searches (primary, stretch, backup)
  2. Refine each to 10-15 results
  3. Research top companies from each search
  4. Apply to best matches within one week
  5. Track applications and follow up

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Market Research

Goal: Understand landscape before committingStrategy:
  1. Broad exploratory searches across role types
  2. Compare salaries by location and experience
  3. Identify trending skills and technologies
  4. Research company cultures and benefits
  5. Save interesting positions for later

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Career Planning

Goal: Determine next career move or pivotStrategy:
  1. Search current role to understand options
  2. Explore adjacent and stretch roles
  3. Identify skill gaps for target positions
  4. Research required certifications or education
  5. Build learning plan based on findings

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Salary Negotiation

Goal: Gather compensation data for negotiationStrategy:
  1. Search your exact role and location
  2. Compare salaries across similar companies
  3. Identify high-paying outliers
  4. Understand total comp (base, equity, bonus)
  5. Use data to support negotiation position

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Common Search Mistakes

Avoid these pitfalls:
  1. Starting too narrow: “Senior React developer with Redux, TypeScript, Next.js, GraphQL, and AWS in Boulder paying $175k+” yields 0 results
  2. Never refining: Accepting the first 500 results without filtering—wastes time reviewing irrelevant jobs
  3. Keyword stuffing: “Python Python developer Python programming Python software” confuses the AI
  4. Ignoring context: Starting fresh each time instead of building on conversation
  5. Being too rigid: Refusing to consider remote when local market is limited
  6. Generic searches: “Tech jobs” or “remote work” without any specifics
  7. Over-filtering too early: Applying all filters at once instead of progressively

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Search Optimization Tips

Explore variations:
  • “Software Engineer” = Developer, Programmer, SWE, Coder
  • “Data Scientist” = ML Engineer, Data Analyst, Research Scientist
  • “Product Manager” = Product Owner, Product Lead, PM
Try:
  • “What other titles exist for this role?”
  • “Show me similar positions with different names”
  • “Are product manager and product owner the same?”
Look for:
  • New grad programs at big companies
  • Rotational programs for career changers
  • Internal mobility at preferred companies
  • Contract-to-hire positions
Search for:
  • “New grad programs at tech companies”
  • “Rotational software engineering programs”
  • “Contract-to-hire data science roles”
  • “Companies with internal mobility policies”
Location tactics:
  • “Remote” often has more positions than any single city
  • Include neighboring cities in metro areas
  • Consider “hybrid” for location flexibility
  • Research cost of living vs. salary
Smart searches:
  • “Remote software engineer or Denver area”
  • “Data analyst in San Francisco Bay Area”
  • “Hybrid positions within 25 miles of Austin”
  • “Remote-first companies hiring nationwide”

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Testing Your Search Strategy

Validate your approach with these checks:
1

Result Quality Check

☑ 80%+ of results are actually relevant ☑ Job titles match what you’re seeking ☑ Salary ranges align with expectations ☑ Requirements are realistic for your background
2

Quantity Sweet Spot

☑ 10-50 results (manageable but sufficient) ☑ Enough variety to compare options ☑ Not so many you can’t review them all ☑ Can realistically apply to 20-50%
3

Refinement Effectiveness

☑ Follow-ups successfully narrow or broaden ☑ AI understands your context ☑ Results improve with each iteration ☑ You’re discovering new insights
4

Actionability

☑ Found 5+ positions you want to apply to ☑ Identified companies to research further ☑ Learned something new about the market ☑ Have clear next steps

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Next Steps

Making the Most of AI Answers

Learn to read, verify, and leverage AI responses

Career Research Best Practices

Comprehensive market exploration strategies

Conversational Follow-ups

Master context-aware search refinement

Start Searching

Put these strategies into practice
Remember: The best search strategy combines specificity with flexibility. Start detailed, refine iteratively, and don’t be afraid to explore unexpected opportunities.
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