Data Scientist

Job Title: Data Scientist

Job Summary

We are seeking a highly skilled Data Scientist to join our analytics and innovation team. The ideal candidate will be responsible for collecting, analyzing, and interpreting large datasets to drive actionable insights and build predictive models. This role requires strong expertise in statistical analysis, machine learning, data visualization, and business problem-solving.

Key Responsibilities

• Collect, clean, and preprocess structured and unstructured data for analysis.
• Develop, test, and deploy machine learning models and predictive analytics solutions.
• Perform advanced statistical analysis to uncover patterns, trends, and insights.
• Build dashboards and data visualizations using tools such as Power BI, Tableau, or Python libraries.
• Collaborate with cross-functional teams to understand business requirements and deliver data-driven solutions.
• Implement NLP, deep learning, or AI-based techniques where required.
• Optimize model performance and ensure scalability in production environments.
• Prepare detailed reports and presentations for stakeholders.
• Work with cloud platforms (AWS/Azure/GCP) for data storage, model deployment, and pipeline creation.
• Stay updated with the latest advancements in data science and AI technologies.

Required Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related field.
• 2–5 years of experience as a Data Scientist or similar role.
• Strong proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Hands-on experience with SQL and database management.
• Expertise in machine learning algorithms, statistical modelling, and data mining techniques.
• Experience with NLP, LLMs, or generative AI is an added advantage.
• Good understanding of cloud ecosystems (AWS/Azure/GCP).
• Strong analytical thinking, problem-solving skills, and attention to detail.
• Excellent communication and documentation skills.

Preferred Qualifications

• Experience working with Big Data technologies (PySpark, Hadoop, Spark).
• Knowledge of MLOps tools like MLflow, Docker, Airflow, or Kubernetes.
• Prior experience in developing end-to-end data pipelines.
• Domain knowledge in finance, retail, healthcare, or manufacturing is a plus.