Senior Data Scientist - Python

4 - 5 years

9 - 14 Lacs

Posted:6 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

About the Role:
We are looking for an experienced Data Scientist with a strong academic background in Data Science and 4-5 years of hands-on industry experience.The ideal candidate should be skilled in developing predictive models, performing data analysis, and applying advanced machine learning techniques to solve Key Responsibilities:
- Analyze large datasets to extract meaningful insights and patterns to support business decisions.- Develop, implement, and optimize machine learning and statistical models for predictive and prescriptive analytics.- Collaborate with engineering, product, and business teams to define and deliver data-driven solutions.- Design and build data pipelines and perform data wrangling using Python, R, or SQL.- Communicate analytical findings through clear data visualizations and storytelling techniques.- Evaluate model performance and improve accuracy and efficiency.- Work with cloud platforms (AWS, Azure, or GCP) to deploy and maintain ML models in production.- Ensure data quality, governance, and compliance with organizational standards.Required Skills and Qualifications:
- Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.- PhD in Data Science or related fields is preferred.- 45 years of relevant experience in Data Science or Machine Learning projects.- Proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow, PyTorch) or R.- Strong understanding of machine learning algorithms, statistical modeling, and data mining techniques.- Experience with data visualization tools such as Power BI, Tableau, or Matplotlib/Seaborn.- Strong SQL skills and experience with data pipelines (Airflow, Spark, etc.- Experience with cloud platforms such as AWS SageMaker, Azure ML, or Google AI Platform.- Excellent analytical, problem-solving, and communication skills.Good to Have:
- Experience with Deep Learning, NLP, or Time Series Analysis.- Exposure to MLOps and CI/CD pipelines for model deployment.- Certifications or project portfolios in Data Science or Machine Learning

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