Data Scientist

About the role

The role owns the end-to-end data science lifecycle, turning complex datasets into predictive insights and production-ready machine learning solutions that drive core business strategy. The team collaborates closely with product managers, data engineers, and software architects to build scalable algorithms that directly influence user growth and system performance.

Responsibilities

• Develop and deploy advanced statistical models, machine learning algorithms, and predictive analytics pipelines in Python
• Collaborate with data engineering to design robust feature stores and scalable ETL pipelines that feed training and inference systems
• Conduct rigorous A/B testing and experimentation analysis to measure the impact of new features and algorithmic updates
• Optimize model performance, latency, and resource utilization for high-throughput production environments
• Communicate complex technical findings and data-driven insights clearly to both technical and non-technical stakeholders

Requirements

• 3-6 years of professional experience in data science, applied statistics, or quantitative machine learning
• Proficiency in Python, SQL, and core scientific computing libraries such as Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow
• Solid understanding of statistical inference, hypothesis testing, experimental design, and predictive modeling techniques
• Experience deploying models into cloud-based production environments using AWS, GCP, or Azure
• Master's or Bachelor's degree in Statistics, Mathematics, Computer Science, or a related quantitative field
• Bonus: Experience with LLMs, NLP applications, or large-scale distributed computing using Spark or Databricks