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- Tasks: Build a web app to discover and score leads using machine learning.
- Company: Join a forward-thinking tech team focused on innovation.
- Benefits: Flexible contract, competitive pay, and hands-on experience with AI.
- Why this job: Make an impact by developing tools that enhance lead generation.
- Qualifications: Proficiency in Python, API integration, and full-stack development required.
- Other info: Short-term project with potential for future opportunities.
The predicted salary is between 30000 - 42000 £ per year.
Project Overview
Build a web application that discovers leads from social media, scores them with ML, and integrates with a CRM. Includes an analytics dashboard.
Core Requirements
- Lead Discovery System
- Connect to Facebook Graph API and Instagram Basic Display API to fetch profiles and posts
- Extract: name, email, company, followers, engagement metrics, recent content
- Fallback: Use Faker-based dummy data generators if API access is limited
- Lead Scoring Engine
- Train a Random Forest classifier (scikit-learn) with 20-30 features:
- Basic: company size, age, followers, engagement rate
- Social: post frequency, hashtag usage, content diversity, sentiment
- Behavioral: website visits, email opens, demo requests (simulated)
- Company: industry, revenue range, funding stage (defaults OK)
- Generate 10,000-20,000 synthetic training samples
- API endpoint returns conversion probability (0-1 score)
Contract duration of 1 to 3 months.
Mandatory skills: Python, fast api, PostgreSQL, Web Application, API Integration, AI Agent Development, Full-Stack Development, Software Debugging
Lead Scoring employer: FreelanceJobs
Contact Detail:
FreelanceJobs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Scoring
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can open doors that applications alone can't.
✨Tip Number 2
Show off your skills! Create a portfolio or a GitHub repo showcasing projects similar to lead scoring or web apps. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions related to Python, API integration, and machine learning. We can help you with mock interviews to boost your confidence!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly.
We think you need these skills to ace Lead Scoring
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights the skills and experiences that match the Lead Scoring role. We want to see your Python prowess, API integration skills, and any experience with machine learning. Don’t just send a generic CV; personalise it for us!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about this project and how your background fits in. We love seeing passion and creativity, so let your personality come through while keeping it professional.
Showcase Relevant Projects: If you've worked on similar projects, make sure to mention them! Whether it's a web app or an ML model, we want to know what you've done. Include links or descriptions of your work to give us a taste of your capabilities.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and ensures you don’t miss out on any updates. Plus, it shows us you’re keen to join the StudySmarter team!
How to prepare for a job interview at FreelanceJobs
✨Know Your Tech Stack
Make sure you’re well-versed in Python, FastAPI, and PostgreSQL. Brush up on how these technologies work together, especially in the context of web applications and API integration. Being able to discuss your experience with these tools will show that you're ready to hit the ground running.
✨Understand Lead Scoring
Familiarise yourself with lead scoring concepts, particularly using machine learning models like Random Forest classifiers. Be prepared to explain how you would approach training a model with various features and what metrics you would consider important for scoring leads.
✨Showcase Your Problem-Solving Skills
Think of examples where you've debugged software or solved complex problems in past projects. Be ready to discuss specific challenges you faced and how you overcame them, especially in relation to full-stack development and AI agent development.
✨Prepare Questions
Have a few thoughtful questions ready about the project and the team. This shows your genuine interest in the role and helps you gauge if the company is the right fit for you. Ask about their approach to integrating social media data or how they measure success in lead scoring.
