Data Science Professional

4 days ago

Bengaluru, Karnataka, India beBeeMachineLearning Full time US$ 1,04,000 - US$ 1,30,878

We are seeking a highly skilled Data Science Professional to join our team. This individual will be responsible for developing and deploying machine learning-driven data validation solutions that ensure data integrity.

The ideal candidate will have strong experience in building ML solutions and collaborating with software teams. They should also be proficient in Python, SQL, and databases, as well as familiar with statistical methods for detecting anomalies and inconsistencies.

The selected candidate will work on various projects, including building scalable anomaly detection systems, collaborating with data engineering teams to enhance data quality frameworks, and driving innovations in MLOps and data monitoring.

Key Responsibilities
  • Develop ML-based data validation and monitoring solutions
  • Analyze large datasets to detect data drift, integrity issues, and emerging quality risks
  • Apply the full ML lifecycle, from exploratory data analysis (EDA) and feature engineering to model selection, training, deployment, and monitoring
  • Experiment with different methodologies to improve model accuracy and reliability
  • Collaborate with data engineering teams to design frameworks for detecting missing, inconsistent, or duplicate data
  • Investigate root causes of data quality issues and propose scalable, automated solutions
Requirements
  • 3+ years of industry experience in building ML solutions and collaborating with software teams
  • Strong experience in machine learning for anomaly detection, data validation, or data quality improvement
  • Proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow)
  • Hands-on experience with SQL and databases (PostgreSQL, Snowflake, MySQL)
  • Strong knowledge of statistical methods (PCA, exponential smoothing) for detecting anomalies, drift, and inconsistencies
PREFERRED QUALIFICATIONS
  • Experience with MLOps tools (MLflow, Kubeflow) for managing data quality models
  • Exposure to big data frameworks (Spark, Kafka) for real-time data validation
  • Familiarity with CI/CD for data pipelines and model deployments

This is an exciting opportunity for a talented data scientist to grow their career and make a meaningful impact in our organization.

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