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.
