Cloud Data Scientist

Azure and Databricks

We are seeking a highly skilled Cloud Data Scientist to join our team. The ideal candidate will have a strong foundation in data science, machine learning, and data engineering, with a particular focus on Azure cloud technologies and Databricks. This role involves leveraging advanced data analytics techniques to extract valuable insights from complex datasets, develop predictive models, and drive data-driven decision-making.

Key Responsibilities:

Data Engineering: Design, develop, and maintain robust data pipelines using Azure Data Factory and Databricks.
Ingest, clean, transform, and enrich large and diverse datasets from various sources.
Optimize data pipelines for performance and scalability.
Data Science: Develop and implement advanced machine learning models using PySpark and other relevant tools.
Conduct exploratory data analysis (EDA) to identify patterns, trends, and anomalies.
Build predictive models for risk assessment, fraud detection, and customer segmentation.
Evaluate model performance and iterate on model improvements.
Data Quality and Governance: Establish and enforce data quality standards and best practices.
Monitor data quality metrics and identify issues.
Implement data governance policies and procedures to ensure data security and privacy.
Collaboration: Collaborate with business stakeholders to understand their needs and translate them into data-driven solutions.
Work closely with data engineers, data analysts, and other team members to deliver high-quality solutions.
Cloud Expertise: Leverage Azure cloud services (Azure Data Lake Storage, Azure Synapse Analytics, Azure Machine Learning) to build scalable and cost-effective data solutions.
Utilize Databricks for data engineering, data science, and machine learning tasks.
SQL Proficiency: Demonstrate strong SQL skills to query and manipulate large datasets.
Optimize SQL queries for performance and efficiency.

Qualifications:

Bachelor's degree in Computer Science or (Statistics, Mathematics, Computer Science, Engineering).
7+ years of experience in data science, machine learning, and data engineering.
Strong proficiency in Python, PySpark, SQL, and machine learning algorithms.
At least 1 - 2 years' of experience in quantitative analytics or data modeling.
Experience with Azure cloud technologies, including Azure Data Factory, Databricks, Azure Data Lake Storage, and Azure Synapse Analytics.
Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms
Fluency in a programming language (Python, C,C++, Java, SQL)
Familiarity with Big Data frameworks and visualization tool
Hands-on experience with data quality and governance practices.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills.
Experience in the insurance industry is highly desired.

If you are a passionate data scientist with a strong technical background and a desire to make a significant impact, we encourage you to apply.

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