Tatvic Analytics - Senior Data Scientist

About Tatvic : Tatvic Analytics is a leading global MarTech and analytics consulting firm, specializing in Google Marketing Platform (GMP) and Google Cloud Platform (GCP) solutions. As a certified Google Partner, we help businesses optimize marketing spend, improve customer engagement, and drive growth through data-driven insights, AI-driven analytics, and advanced marketing technology. Our expertise spans Google Analytics, programmatic campaign management, conversion rate optimization, cloud-based marketing activation, and location-based services. With a strong focus on innovation and technology, we work with leading brands across eCommerce, BFSI, and digital-first industries. At Tatvic, you'll be part of a dynamic team that leverages cutting-edge tools, data science, and automation to solve complex digital challenges and create real business impact. Job description : Responsibilities of a Data Scientist : Responsibilities w.rt Customer : - Keep the promises made to the customer in terms of deliverables. - Designing solutions using data science platforms. - Bird's eye view of the Platform to create an effective solution. - Identify features which would matter and ensure that logic for feature selection is clear to all. - Use Auto ML as well as individual algorithms for effective solutions. - Display or export the output into a visualization platform. - Create an API which can be used to access the model for query. - Optimize the model to increase the effectiveness with proper data cleansing and feature engineering. - Create a POC for providing data insight for the customer at a short notice. Innovation and Asset building Responsibilities : - Design and Build reusable solution which can be used for multiple customers. - Create clear documentation on architecture and design concepts used in the project. - Provide assistance to other team members to learn cloud platform by training and creating the presentation. - Maintain coding standards & Building reusable code and libraries for future use. - Stay updated with new innovations in data science. - Explore the usage of data science in various business and web analytics applications. Technical Skills : - Data Handling : Manage data from diverse sources, including structured tables, unstructured text, images, videos, and streaming/real-time data. - Feature Engineering : Identify and select relevant features with transparent and explainable logic. Model Development : - Select and build models based on problem requirements, using pre-trained models, AutoML, or custom algorithms. - Apply advanced modeling techniques like CNNs for image processing, RCNNs, YOLO for object detection, and RAGs and LLM tuning for text and search-related tasks. - Optimize models with hyperparameter tuning, Bayesian optimization, and appropriate evaluation strategies. Model Evaluation : - Assess model performance using metrics suited for data type and problem type : 1. For categorical data : Precision, Recall, F1 Score, ROC-AUC, and Precision-Recall curves. 2. For numerical data : Metrics like Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Squared Error (MSE), and R-squared (R- ). - Deployment & MLOps : Deploy models for batch or real-time predictions using MLOps frameworks, leveraging tools such as VertexAI and Kubeflow for efficient and scalable deployment pipelines. - Innovation : Stay current with trends in AI and data science, including LLMs, grounding techniques, and innovations in temporal and sequential data modeling. Code Practices & Engineering : - Write clean, maintainable, and scalable code following industry best practices. - Implement error handling, logging, and monitoring to ensure reliability in production systems. - Collaborate with other teams to integrate data science models into broader system architectures. - Performance Optimization : Optimize model and data processing pipelines for computational efficiency and scalability. - Documentation & Reusability : Maintain comprehensive technical documentation for all solutions. Functional Competencies : - Applying Technical knowledge (SQL/no SQL/ML/DL). - Python / Libraries/Packages/ API/Web Services. - Data Analysis. - Cloud And Infra Services / Monitoring & Debugging/ Orchestration Frameworks. - Solution/Architecture Design. (ref:hirist.tech)

Location: ahmedabad, IN

Posted Date: 5/4/2025