Role Overview
We are seeking a Freelance Data Scientist with availability to handle multiple projects, who can lead complex data initiatives, design robust models, and influence product and business decisions through data. This position starts as a part-time position and has the potential to become a full-time employee depending on performance. Hourly salary will be determined based on experience and skill level.
This role requires deep expertise in statistics, machine learning, and data modeling, along with the ability to mentor others, define best practices, and work closely with engineering, product, and leadership teams. Exposure to modern AI and LLM-based systems is a strong plus.
Key Responsibilities
- Lead end-to-end data science projects from problem definition to production deployment
- Design, build, and optimize advanced statistical and machine learning models
- Analyze large-scale, structured and unstructured datasets to generate actionable insights
- Define data science best practices, modeling standards, and evaluation frameworks
- Design and analyze experiments (A/B tests, causal analysis, hypothesis testing)
- Partner with product, engineering, and business stakeholders to influence strategy and roadmap
- Review and improve existing models for accuracy, scalability, and robustness
- Mentor junior data scientists and review analytical work
- Clearly communicate complex findings to senior stakeholders and leadership
- Ensure data quality, reproducibility, and documentation across projects
Required Skills & Qualifications
Core Technical Expertise
- Expert-level proficiency in Python (Pandas, NumPy, Scikit-learn)
- Strong foundation in statistics, probability, and linear algebra
- Extensive experience with machine learning techniques (regression, classification, clustering, time-series, anomaly detection)
- Strong hands-on experience with SQL and relational databases
- Experience working with large datasets and complex data pipelines
- Deep understanding of model evaluation, bias/variance trade-offs, and performance monitoring
- Proven experience taking models from development to production
Nice to Have (AI & LLM Experience)
- Hands-on experience with Large Language Models (LLMs) such as GPT, Claude, LLaMA, or similar
- Experience integrating LLM APIs into production systems
- Strong understanding of prompt engineering and output evaluation
- Experience with embeddings, semantic search, and vector similarity techniques
- Knowledge of Retrieval-Augmented Generation (RAG) architectures
- Experience working with vector databases (Pinecone, FAISS, Weaviate, Milvus, etc.)
- Awareness of AI risks such as hallucinations, bias, security, privacy, and cost optimization
Leadership & Soft Skills
- Strong ownership and decision-making ability
- Proven ability to mentor and guide team members
- Excellent communication skills with both technical and non-technical audiences
- Business-first mindset with the ability to balance speed, accuracy, and impact
- Comfortable working in ambiguous, fast-moving environments
Education
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field
- Equivalent real-world experience is highly valued