Data Scientist

Collect, clean, and prepare structured and unstructured data from various sources.

Develop and implement machine learning models, statistical algorithms, and predictive analytics.

Perform exploratory data analysis (EDA) and extract meaningful insights to support decision-making.

Build data pipelines and automate model workflows in collaboration with data engineering teams.

Communicate insights clearly to stakeholders through dashboards, visualizations, and presentations.

Monitor model performance, perform retraining, and maintain model accuracy and stability.

Work closely with product, engineering, and business teams to identify opportunities for data-driven improvements.

Stay updated with the latest research, tools, and technologies in data science and AI.

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science or related fields.

Strong proficiency in Python or R, with experience in data libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar frameworks.

Expertise in machine learning algorithms, model evaluation, and optimization.

Experience with SQL and working with large datasets.

Knowledge of data visualization tools such as Tableau, Power BI, or matplotlib/seaborn.

Strong understanding of statistical concepts and their application in business scenarios.

Ability to translate complex data into clear, actionable insights.

Experience with big data technologies (Spark, Hadoop, Databricks).

Exposure to cloud platforms (AWS, Azure, GCP).

Knowledge of NLP, deep learning, or advanced ML techniques.

Experience in domain-specific analytics (BFSI, retail, healthcare, etc.).

Familiarity with MLOps and deploying models in production environments.

Strong analytical and problem-solving skills.

Excellent communication and storytelling ability.

Detail-oriented with a focus on data accuracy.

Ability to work independently and collaboratively in a cross-functional team.

Responsibilities

Qualifications