lead data scientist
4 weeks ago
Key Responsibilities:
- Design and Oversee ETL Pipelines: Lead the design, implementation, and optimization of Extract, Transform, Load (ETL) processes to ensure efficient and accurate data flow from various sources to analytical platforms.
Data Analysis and Modeling: Conduct advanced data analysis and develop predictive and prescriptive models using Python, leveraging libraries like pandas, NumPy, scikit-learn, and TensorFlow.
Database Management and Querying: Design and manage relational databases, write and optimize SQL queries for data extraction and transformation, and ensure database integrity and performance.
Data Visualization and Reporting: Create interactive dashboards and insightful visualizations using Power BI to communicate findings and support data-driven decision-making across the organization.
Project Management and Collaboration: Collaborate with cross-functional teams, including data engineers, business analysts, and stakeholders, to align data analytics projects with organizational goals and ensure timely delivery.
Mentoring and Skill Development: Provide technical guidance and mentorship to junior data scientists, fostering skill development in Python, SQL, ETL processes, and analytics best practices.
Continuous Improvement: Identify opportunities to enhance analytics workflows, tools, and strategies to improve data accessibility, analysis, and overall business impact.
Qualifications:
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
Minimum of 5 years of hands-on experience in data analytics, machine learning, or similar roles. Experience in Medical Device or Pharmaceutical industry a plus.
- Minimum of 2 years experience in team leadership or management roles required.
Proven expertise in designing, implementing, and optimizing ETL pipelines for data integration and transformation across diverse data sources.
Strong programming skills in Python, including experience with libraries such as pandas, NumPy, scikit-learn, and TensorFlow for data analysis and machine learning.
Demonstrated ability to write and optimize complex SQL queries, manage relational databases, and ensure data quality and integrity.
Hands-on experience creating interactive dashboards and visualizations in Power BI to translate data insights into actionable business decisions.
A solid track record in designing and deploying predictive and prescriptive models to solve real-world business challenges.
Experience leading and mentoring data teams, fostering a collaborative environment, and guiding junior data scientists in technical skill development.
Strong project management capabilities, with excellent communication skills to collaborate with cross-functional teams and effectively present findings to stakeholders.
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