| We are looking for an experienced Data Scientist to join our analytics team in Bangalore. The ideal candidate will have a strong background in statistical analysis, machine learning, data visualization, and big data technologies. You will work closely with business stakeholders and engineering teams to design data-driven solutions that enhance decision-making and drive innovation. Key Skills: Python, R, SQL, Machine Learning, Deep Learning, NLP, TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, Data Visualization (Power BI / Tableau / Matplotlib / Seaborn), Statistics, Big Data (Spark, Hadoop), Data Cleaning, Feature Engineering, Model Deployment (Flask / FastAPI / Streamlit), Cloud (AWS, Azure, GCP). Roles and Responsibilities: Collect, clean, and preprocess large datasets from multiple sources. Build predictive and prescriptive machine learning models using statistical techniques. Develop and deploy data models and automation pipelines in production environments. Perform exploratory data analysis (EDA) to uncover insights and trends. Communicate findings through dashboards, reports, and visualizations. Collaborate with data engineers and business analysts to translate business problems into analytical models. Evaluate model performance and fine-tune parameters for optimal results. Stay updated on emerging technologies, AI frameworks, and data science best practices. Technical Environment: Programming: Python, R, SQL ML/DL Libraries: TensorFlow, Keras, PyTorch, Scikit-learn Data Tools: Pandas, NumPy, Spark, Hadoop Visualization: Power BI, Tableau, Matplotlib, Seaborn Deployment: Flask, FastAPI, Docker Cloud Platforms: AWS Sagemaker, Azure ML, Google AI Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related field. Minimum 8 years of experience in data science, analytics, or AI development. Strong understanding of machine learning algorithms, data pipelines, and MLOps. Excellent communication and storytelling abilities to present insights effectively. Nice to Have: Experience with NLP, Computer Vision, or Generative AI projects. Familiarity with AutoML tools and advanced statistical modeling. Knowledge of DevOps and CI/CD practices for data pipelines. | 
