Neural Net Data Scientist

Neural Network Data Scientist

W2 Contract 3 Months

Remote, USA

$73-$83/hr

We are seeking a Data Scientist with strong expertise in neural networks and machine learning to help quantify and optimize the value of participants in the Tinder ecosystem.

This position requires strong skills in Python, PyTorch, machine learning, and graph neural networks (GNNs).

You will focus on building models that go beyond traditional customer LTV to capture network-level value:

• Your work will help measure and properly value the contributions of all user groups in our marketplace, guiding smarter marketing spend and platform investment.

What You’ll Do

• Develop and deploy models using graph neural networks and machine learning to quantify Network LTV across Tinder’s two-sided marketplace.
• Translate complex business problems (e.g., valuing non-paying users who drive indirect revenue) into measurable data science frameworks.
• Build models that capture interactions between user groups (buyers/sellers, male/female, supply/demand) and optimize ecosystem-wide outcomes.
• Collaborate with marketing, analytics, and product teams to inform customer acquisition strategies and ROI measurement.
• Leverage Python and PyTorch to implement scalable ML solutions for marketplace and network analysis.
• Present insights and findings to technical and non-technical stakeholders.

What We’re Looking For (Must-Haves)

• Strong proficiency in Python for data science and ML development.
• Experience with PyTorch for neural nets / machine learning.
• Hands-on expertise with neural networks, especially graph neural nets (GNNs).
• Solid grounding in machine learning fundamentals (predictive modeling, optimization, statistical analysis).
• Experience applying ML to complex network or marketplace problems.

Nice-to-Haves

• Experience with customer lifetime value (LTV) or network LTV modeling.
• Prior work in two-sided marketplaces or ecosystem-based platforms (e.g., Amazon, Uber, Airbnb, Expedia).
• Background in marketing analytics or financial analytics.
• Experience with large-scale experimentation (A/B testing, causal inference).

Who You Are

• A technically strong data scientist with a deep ML/neural net toolkit.
• Curious about understanding indirect value flows in marketplaces and ecosystems.
• Able to bridge mathematical modeling and business impact.
• A collaborative problem-solver who can work with data, marketing, and product stakeholders.