Data Scientist

Experience Level: 2-5 years
Location: Bengaluru
Education: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or related fields. A strong academic pedigree is highly preferred.

Overview: We are seeking a talented and motivated Data Scientist to join our team. The ideal candidate will have 2-5 years of hands-on experience in the development and deployment of Machine Learning (ML) projects. Exposure to Computer Vision and Natural Language Processing (NLP), especially Large Language Models (LLMs), will be a significant advantage.

Key Responsibilities:

- Develop, deploy, and optimize ML models for prediction and forecasting tasks on tabular/text datasets.

- Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.

- Perform data preprocessing, feature engineering, and exploratory data analysis (EDA) to support model development.

- Build and deploy end-to-end ML pipelines, including model training, evaluation, and serving in production environments.

- Monitor and maintain deployed models to ensure robustness, scalability, and performance over time.

- Implement feedback loop into prediction.

- Drive innovation: Explore, experiment with, and integrate cutting-edge ML techniques and frameworks into projects.

- Document workflows, methodologies, and findings for both technical and non-technical stakeholders.

Key Skills and Qualifications:

Core Expertise:

- Proficiency in Python and popular ML libraries such as Scikit-learn, TensorFlow, or PyTorch.

- Strong understanding of supervised and unsupervised ML algorithms.

- Hands-on experience with model deployment tools such as Docker, Flask, FastAPI, or cloud-based ML services (AWS SageMaker, GCP Vertex AI, etc.).

- Proficiency in working with structured/unstructured data, SQL.

Added Advantage:

- Experience in Computer Vision (e.g., OpenCV, YOLO, or related frameworks).

- Exposure to NLP/LLMs (e.g., Hugging Face, GPT, or BERT).

- Familiarity with MLOps practices, CI/CD pipelines for ML, and model monitoring (MLFlow).

General Skills:

- Strong problem-solving skills and attention to detail.

- Excellent communication skills to convey technical concepts to diverse audiences.

- Ability to work in a fast-paced environment and manage multiple priorities effectively.