Freelance Data Scientist

Looking for aFreelance Data Scientistto join a team of rockstar developers. The candidate should have a minimum of 4+ yrs. of experience.There are multiple openings. If you're looking for freelance/ part time opportunity (along with your day job) & a chance to work with the top 0.1% of developers in the industry, this one is for you You will report into IIT'ans/BITS grads with 10+ years of development experience + work with F500 companies (our customers).Company Background- We are a multinational software company that is growing at a fast pace. We have offices in Florida & New Delhi. Our clientele spreads across the US, Australia & APAC. To give you a sense of our growth rate, we've added 70+ employees in the last 6 weeks itself and expect another 125+ by the end of Q4 2025.Key Responsibilities:•Product Development & Deployment: Lead end-to-end development and productionization of data science solutions from ideation through production deployment•LLM Integration: Design, implement, and integrate various Large Language Models (LLMs) into production systems using Python•Advanced Modeling: Build and optimize models using LightGBM, XGBoost, and cutting-edge foundation models including TimeGPT and Lag-Llama•Feature Engineering: Conduct advanced feature engineering and deep-dive analysis to identify meaningful patterns and insights that enhance model performance and robustness•Model Optimization: Build, test, and optimize machine learning models for production environments with focus on reliability, scalability, and performance•Time Series Forecasting: Develop sophisticated forecasting solutions leveraging both traditional and foundation model approaches•Stakeholder Collaboration: Work closely with product managers, engineers, and business stakeholders to translate business problems into technical solutions•Production Monitoring: Implement monitoring and maintenance strategies to ensure model performance and reliability in productionRequired Qualifications:•Experience: 4-5 years of hands-on experience in data science roles•Production Experience: Demonstrated experience in productionizing data science solutions from scratch, including deployment and monitoring•Python Expertise: Advanced proficiency in Python with strong software engineering practices•Gradient Boosting Models: Deep knowledge and hands-on experience with LightGBM and XGBoost, including hyperparameter tuning and optimization•Foundation Models: Practical experience with modern foundation models such as TimeGPT and Lag-Llama for time series forecasting•LLM Integration: Hands-on experience integrating different types of Large Language Models (GPT, Claude, open-source models, etc.) into production systems•Feature Engineering: Deep expertise in feature engineering, data exploration, and extracting actionable insights from complex datasets•Model Development: Strong understanding of machine learning algorithms, ensemble methods, model evaluation, and optimization techniques•Technical Stack: Experience with ML frameworks (scikit-learn, TensorFlow, PyTorch) and cloud platforms (AWS/Azure/GCP)Preferred Qualifications•Industry Experience: Background in FMCG (Fast-Moving Consumer Goods) or retail sectors is a strong plus•Time Series Expertise: Experience with classical time series methods (ARIMA, Prophet) alongside modern foundation models•MLOps: Experience with MLOps tools and practices (Docker, Kubernetes, CI/CD pipelines)•API Development: Experience building and deploying APIs for ML models•Big Data: Familiarity with big data technologies (Spark, Hadoop) and data warehousing solutions•A/B Testing: Experience designing and analyzing experimentsTechnical SkillsCore Programming & ML• Programming: Python (required), SQL• ML/AI: Machine Learning, Deep Learning, NLP, LLM integration• Gradient Boosting: LightGBM, XGBoost, CatBoost• Foundation Models: TimeGPT, Lag-Llama, and other time series foundation modelsFrameworks & Libraries• ML Frameworks: scikit-learn, PyTorch, TensorFlow• LLM Tools: Hugging Face, LangChain, OpenAI API• Data Processing: Pandas, NumPy, Polars• Forecasting: Prophet, statsmodels, Nixtla (TimeGPT)Infrastructure & DevOps• Cloud Platforms: AWS/Azure/GCP• Containerization: Docker, Kubernetes• Version Control: Git, MLflow• Data Pipelines: Airflow, PrefectWhat we need-~35 hours of work per week.-100% remote from our side-You will be paid out every month.-Min 4yrs of experience-Please apply only if you have a 100% remote job currently-If you do well, this will continue for a long time