Senior Data Scientist
New
J
JobgetherSecurity & IT
Based in IndiaFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English proficiency at a minimum B2 level.
- Experience
- At least 5 years of professional experience
- Required Skills
- PythonSQLMachine LearningSparkDatabricksDeep LearningMLOps
Requirements
- Degree in Mathematics, Computer Science, Machine Learning, or a related technical field.
- At least 5 years of professional experience in data science, with a proven track record of building and architecting production-level data solutions.
- Advanced Python skills including NumPy, pandas, scikit-learn, and PyTorch or TensorFlow.
- Strong knowledge of statistics, experimental design, and causal inference.
- Proven experience developing and scaling complex ML/DL models for production use.
- Experience with ML experimentation and tracking platforms such as MLflow, W&B, or Databricks ML.
- Advanced SQL skills for large-scale data manipulation.
- Strong understanding of MLOps principles including deployment, monitoring, model drift, and retraining.
- Experience with Spark, Databricks, or other big-data platforms.
- Hands-on experience with cloud ML platforms such as Azure ML, SageMaker, or Vertex AI.
- English proficiency at a minimum B2 level.
Responsibilities
- Design, develop, and scale advanced machine learning and deep learning models for production environments.
- Apply statistical methods, experimental design, and causal inference to solve complex analytical problems.
- Conduct and manage ML experimentation using tools such as MLflow, Weights & Biases, and Databricks ML.
- Develop efficient data workflows and perform large-scale data manipulation using advanced SQL.
- Leverage big-data technologies such as Spark and Databricks to optimize model training and scoring.
- Implement and improve MLOps workflows covering model registries, deployment, monitoring, drift management, and retraining.
- Work with cloud-based machine learning platforms such as Azure ML, Amazon SageMaker, or Google Vertex AI.
- Translate complex technical concepts into recommendations for non-technical audiences.
- Mentor junior and mid-level engineers and establish strong engineering practices.
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