Senior Data Science Engineer

Job Purpose

As a Senior Data Science Engineer, you will be a key contributor in advancing our data science and engineering capabilities. This role requires a seasoned professional with a deep understanding of machine learning, data engineering, and software development. Y

You will lead the design and implementation of complex data science solutions, mentor junior team members, and collaborate with cross-functional teams to deliver innovative, scalable, and impactful data-driven solutions.

Key Result Responsibilities

1. Advanced Model Development:Lead the design, development, and deployment of advanced machine learning models to address complex business problems.
2. Optimize models for performance, scalability, and efficiency.
3. Data Engineering Leadership:Provide technical leadership in the design and implementation of robust data pipelines for efficient ETL processes.
4. Collaborate with data engineers to ensure data availability, quality, and reliability.
5. Feature Engineering and Data Preprocessing:
6. Guide the development of feature engineering pipelines to extract relevant information from diverse and large datasets.
7. Work closely with data scientists to identify and create features that enhance model performance.
8. Scalability and Optimization:Drive efforts to scale data science solutions to handle large volumes of data efficiently.
9. Implement optimization techniques for algorithms, models, and data processing workflows.
10. Model Governance and Monitoring:Establish and enforce best practices for model governance, monitoring, and performance tracking.
11. Implement continuous monitoring and improvement processes for deployed models.
12. Collaboration and Mentoring:Collaborate with cross-functional teams, providing technical expertise and guidance on data science and engineering projects.
13. Mentor and coach junior team members, fostering a culture of continuous learning and development.
14. Documentation and Knowledge Sharing:Ensure clear documentation of code, data pipelines, and model implementations for reproducibility.
15. Facilitate knowledge sharing within the team and across the organization.
16. Strategic Contributions:Collaborate with leadership to align data science and engineering initiatives with strategic business goals.
17. Stay abreast of industry trends and emerging technologies, providing recommendations for technology adoption

Key Result Responsibilities-Continued

Qualifications (Academic, training, languages)

Work Experience

• Master's or Ph.D. in Computer Science, Data Science, or a related discipline.
• 7+ years of professional experience in data science, machine learning, and data engineering.
• Expertise in programming languages such as Python, Java, or similar.
• In-depth knowledge of machine learning algorithms, statistical modeling, and data engineering concepts.
• Proven experience in designing and implementing scalable data pipelines.
• Demonstrated leadership and mentoring abilities.
• Strong problem-solving and analytical skills.
• Excellent communication skills for both technical and non-technical audiences.