Mid Data Scientist

Job Description

We are looking for 5+years experienced candidates for this role. Job Description Strong knowledge of statistical modeling, machine learning, deep learning and GenAI. Proficiency in Python and experience optimizing code for performance. Experience with data preprocessing, feature engineering, data visualization and hyperparameter tuning. Solid understanding of database concepts and experience working with large datasets. Experience deploying and scaling machine learning models in a production environment. Familiarity with machine learning operations (MLOps) and related tools. Good understanding of Generative AI concepts and LLM finetuning. Excellent communication and collaboration skills. Bachelor's or Master's degree in a quantitative field such as statistics, mathematics, computer science, or a related area. Responsibilities include: Lead the development and deployment of machine learning/deep learning models to address key business challenges. Apply statistical modeling, data preprocessing, feature engineering, machine learning, and deep learning techniques to build and improve models. Have expertise in at least two of the following areas: computer vision, predictive analytics, natural language processing, time series analysis, recommendation systems. Expertise in GenAI models is a must. Design, implement, and optimize data pipelines for model training and deployment. Experience with any one of the model serving frameworks (e.g.,TensorFlow Serving, TorchServe, KServe, or similar). Design and implement APIs for model serving and integration with other systems. Collaborate with cross-functional teams to define project requirements, develop solutions, and communicate results. Mentor junior data scientists, providing guidance on technical skills and project execution. Stay up-to-date with the latest advancements in data science and machine learning, particularly in generative AI, and evaluate their potential applications. Communicate complex technical concepts and analytical findings to both technical and non-technical audiences. Primary Skills : Python Data Science concepts Generative AI Pandas, NumPy, Matplotlib Artificial Intelligence Statistical Modeling Machine Learning, Natural Language Processing (NLP), Deep Learning Model Serving Frameworks (e.g., TensorFlow Serving, TorchServe) MLOps(e.g; MLflow, Tensorboard, Kubeflow etc) Computer Vision Predictive Analytics Time Series Analysis Anomaly Detection Recommendation Systems SQL Proficent in any of Cloud Computing Platforms (e.g., AWS, Azure, GCP)