Role Overview
We are seeking a skilled Data Scientist with 2–4 years of experience to build scalable data solutions, develop machine learning models, and transform complex data into actionable business insights.
What You Will Do
Design, build, and maintain scalable data pipelines and data platforms, collect, clean, transform, and analyze large datasets, develop and deploy machine learning models to solve business problems.
Why It Might Be a Fit
The ideal candidate should have a strong foundation in data engineering, analytics, statistics, and machine learning, and experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud.
Requirements
- Strong proficiency in Python and SQL
- Experience designing and developing ETL/ELT pipelines
- Hands-on experience with data processing frameworks such as Apache Spark
- Experience with relational and NoSQL databases
- Strong understanding of data warehousing, data lakes, and dimensional modeling
- Experience working with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud
- Experience with workflow orchestration tools such as Apache Airflow
- Proficiency in data analysis using Pandas and NumPy
- Experience building and deploying machine learning models using Scikit-learn
- Strong knowledge of statistics, probability, hypothesis testing, and predictive analytics
- Experience with feature engineering, model evaluation, and model optimization
- Data visualization experience using Power BI or Tableau
- Experience with version control using Git
- Understanding of data quality, governance, and security best practices
- Experience in Insurance and Lending domains will be preferred
To apply for this job please visit linkedin.com.
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