Job Title: Data Scientist
Experience: 3-5 years
Location: Bangalore, India
Employment Type: Full-Time
Role Overview:
We are looking for a highly motivated and skilled Data Scientist with 3-5 years of experience in data science, analytics, and machine learning. The ideal candidate will have hands-on experience in building models, working with large datasets, and deploying data-driven solutions to solve business problems.
Key Responsibilities:
- Develop and implement machine learning models for customer segmentation, profiling, and demand forecasting.
- Analyze structured and unstructured data to generate actionable business insights.
- Work with large-scale datasets, perform data cleaning, and apply feature engineering techniques.
- Design, develop, and deploy predictive analytics solutions using cloud-based platforms like AWS.
- Collaborate with cross-functional teams, including data engineers, product managers, and business stakeholders, to translate business needs into data-driven solutions.
- Utilize statistical analysis, data visualization, and A/B testing techniques to support decision-making.
- Optimize and fine-tune ML models for scalability and performance.
Required Skills and Qualifications:
- Bachelor's or Master’s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
- 3-5 years of hands-on experience in data science, machine learning, and analytics.
- Proficiency in Python or R for data analysis and model building.
- Strong knowledge of machine learning frameworks such as Scikit-Learn, TensorFlow, or PyTorch.
- Experience working with cloud platforms like AWS (EC2, SageMaker), Azure, or GCP.
- Expertise in SQL and working with relational databases like MySQL, PostgreSQL, etc.
- Familiarity with big data technologies such as Spark, Databricks, and Hadoop is a plus.
- Experience in data visualization tools like Tableau, Power BI, or Matplotlib.
- Strong problem-solving skills and the ability to translate business problems into analytical solutions.
- Excellent communication and collaboration skills.
Nice to Have:
- Experience with NLP, time-series forecasting, and deep learning techniques.
- Exposure to MLOps practices for deploying and maintaining ML models in production.
- Familiarity with CI/CD pipelines for ML model deployment.
