Junior Data Scientist

We are seeking a highly motivated Junior Data Scientist with 2 years of hands-on experience to join our dynamic data team. In this role, you will work closely with senior data scientists, engineers, and product stakeholders to build intelligent solutions using machine

learning, deep learning, and cutting-edge Gen AI technologies. You will contribute to developing end-to-end data-driven systems that power product features, drive insights, and enable smarter decision-making across the business.

Key Responsibilities

• Collaborate with cross-functional teams to define data problems and translate them into analytical or predictive modeling tasks.
• Perform data wrangling, feature engineering, and exploratory data analysis using Python and SQL.
• Build and evaluate machine learning models for tasks such as classification, regression, clustering, and recommendation.
• Apply deep learning techniques using frameworks like TensorFlow or PyTorch for unstructured data such as images, audio, or text.
• Work on Natural Language Processing (NLP) use cases like text classification, sentiment analysis, and named entity recognition.
• Experiment with Generative AI and Large Language Models (LLMs) (e.g., OpenAI, HuggingFace) to build intelligent assistants or automate content generation.
• Deploy and monitor models in production, ensuring reliability and scalability.
• Document your work clearly and communicate findings to both technical and non-technical stakeholders.

Key Requirements

Must-Have Skills

• Programming: Strong proficiency in Python and related data science libraries (Pandas, NumPy, Scikit-learn, etc.)
• Data Manipulation: Experience in writing efficient SQL queries and handling structured databases.
• Machine Learning: Solid understanding of supervised and unsupervised learning algorithms.
• Deep Learning: Exposure to frameworks like TensorFlow or PyTorch.
• NLP: Familiarity with core NLP tasks and tools such as NLTK, spaCy, or HuggingFace Transformers.
• Gen AI / LLMs: Hands-on experience or projects involving prompt engineering, fine-tuning, or embedding-based retrieval.
• Version Control: Working knowledge of Git and collaborative development workflows.

Good-to-Have

• Experience with cloud platforms (AWS, GCP, or Azure).
• Familiarity with model deployment tools (Flask, FastAPI, Streamlit).
• Exposure to MLOps practices or tools (MLflow, Weights & Biases, etc.).
• Experience working with APIs and third-party data sources.

Candidate Profile

• Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Engineering, or a related field.
• 1–2 years of industry or academic experience in data science or machine learning projects.
• Strong problem-solving skills and an analytical mindset.
• Enthusiasm for learning new tools, frameworks, and domains.
• Excellent communication and collaboration skills.