Data Scientist

Role : Data Scientist Location : Bangalore (Remote) Job Description : We are looking for Software/Backend/Data Scientists with a passion for developing robust machine learning (ML) systems and working in a collaborative environment. The ideal candidates will have strong Python skills, a background in software engineering, and experience working across the end-to-end ML lifecycle. As leaders, you will be responsible for reviewing code, guiding problem-solving sessions, and communicating technical knowledge to both technical and non-technical teams. Key Responsibilities : - Lead the design, development, and deployment of machine learning models, ensuring they meet the requirements of different stakeholders across the organization. - Collaborate with cross-functional teams (management, data engineering, brand teams) to build scalable, production-ready machine learning pipelines. - Develop and implement model serving pipelines and automate processes using MLOps frameworks (e.g., MLflow, SageMaker, etc.). - Review peers' code and contribute to team-wide problem-solving discussions, encouraging collaboration and adherence to best practices. - Apply distributed computing frameworks such as Snowpark or PySpark to scale data processing and model training efforts. - Build and refine machine learning models ranging from simple linear/logistic regression to deep learning architectures, depending on the needs of the project. - Design and implement strategies for training models on imbalanced datasets Utilize appropriate training schemas for unbiased model training (and perform model tuning for optimal performance. - Articulate model performance and evaluation metrics to both technical and non-technical stakeholders, ensuring model decisions are well-understood. - Diagnose model/data drift and implement time-wise tracking of model performance to ensure reliability over time. Required Skills and Qualifications : - Strong Python skills, with a focus on developing efficient and scalable machine learning pipelines. - Demonstrated experience working with distributed computing frameworks like Snowpark or PySpark. - Software engineering background with knowledge of best practices in software design, testing, and deployment. - Proven experience in the end-to-end machine learning lifecycle, from data preprocessing to model deployment. - Experience with all sizes of machine learning models, from linear/logistic regression to deep learning. - Experience handling largely imbalanced training datasets and developing strategies for effective learning. - Proficiency with training schemas for unbiased model evaluation and tuning, such as cross-validation techniques. - Strong problem-solving skills and the ability to contribute to technical discussions in a collaborative environment. - Familiarity with MLOps frameworks for model tracking, deployment, and automation of pipelines. - Experience working with Dataiku or other data science-enabling tools (e.g., SageMaker, Databricks). (ref:hirist.tech)

Location: in, IN

Posted Date: 11/27/2024