Looking for a Freelance Data Scientist to 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 production
Required Qualifications :
Experience : 4-5 years of hands-on experience in data science rolesProduction Experience : Demonstrated experience in productionizing data science solutions from scratch, including deployment and monitoringPython Expertise : Advanced proficiency in Python with strong software engineering practicesGradient Boosting Models : Deep knowledge and hands-on experience with LightGBM and XGBoost, including hyperparameter tuning and optimizationFoundation Models : Practical experience with modern foundation models such as TimeGPT and Lag-Llama for time series forecastingLLM Integration : Hands-on experience integrating different types of Large Language Models (GPT, Claude, open-source models, etc.) into production systemsFeature Engineering : Deep expertise in feature engineering, data exploration, and extracting actionable insights from complex datasetsModel Development : Strong understanding of machine learning algorithms, ensemble methods, model evaluation, and optimization techniquesTechnical 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 plusTime Series Expertise : Experience with classical time series methods (ARIMA, Prophet) alongside modern foundation modelsMLOps : Experience with MLOps tools and practices (Docker, Kubernetes, CI / CD pipelines)API Development : Experience building and deploying APIs for ML modelsBig Data : Familiarity with big data technologies (Spark, Hadoop) and data warehousing solutionsA / B Testing : Experience designing and analyzing experimentsTechnical Skills
Core Programming & ML
Programming : Python (required), SQLML / AI : Machine Learning, Deep Learning, NLP, LLM integrationGradient Boosting : LightGBM, XGBoost, CatBoostFoundation Models : TimeGPT, Lag-Llama, and other time series foundation modelsFrameworks & Libraries
ML Frameworks : scikit-learn, PyTorch, TensorFlowLLM Tools : Hugging Face, LangChain, OpenAI APIData Processing : Pandas, NumPy, PolarsForecasting : Prophet, statsmodels, Nixtla (TimeGPT)Infrastructure & DevOps
Cloud Platforms : AWS / Azure / GCPContainerization : Docker, KubernetesVersion Control : Git, MLflowData Pipelines : Airflow, PrefectWhat we need
~35 hours of work per week.100% remote from our sideYou will be paid out every month.Min 4yrs of experiencePlease apply only if you have a 100% remote job currentlyIf you do well, this will continue for a long time