Senior Data Engineer

Key Performance Indicators (KPIs) for the role:

Over the next 12 months, this role’s success will be measured on:

1. Successful deployment of data science models into production.
2. Improvement in model performance metrics (e.g., accuracy, precision, recall).
3. Effective data-driven decision-making supported by predictive analytics and statistical models.
4. Timely identification and mitigation of model drift.
5. Effective collaboration with cross-functional teams.
6. Mentorship and development of junior team members.

KEY JOB REQUIREMENTS:

In this role, you will be successful if you have:

Experience:

1. 5+ years of experience in data science.
2. Strong understanding of data science techniques, including statistical modeling and data analytics.
3. Experience with data science libraries (e.g., NumPy, pandas, scikit-learn).

Skills & Competencies:

Must Have:

1. Proficiency in Python, R, or other relevant programming languages.
2. Proficiency in working with large datasets, data wrangling, and data preprocessing.
3. Ability to work independently and lead projects from inception to deployment.
4. Experience with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP, Azure).