Team Lead Data Scientist

SWATX; Riyad Al Khabra; On-site; USD 60,000 - 90,000; Full time

Job summary

A leading company in the telecommunications sector is seeking a Team Lead Data Scientist. In this role, you will lead a team of data scientists to develop advanced machine learning models while collaborating closely with data engineering teams. You are expected to leverage your expertise in Python, SQL, and various big data technologies to optimize data-related processes and deliver impactful data solutions.

Qualifications

• 5+ years of hands-on experience in data science.
• Proven track record in architecting and delivering robust data platforms.
• Local GCC experience, preferably Saudi projects.

Responsibilities

• Lead and mentor a team of data scientists and engineers.
• Develop and implement machine learning models for predictive and prescriptive analytics.
• Collaborate with stakeholders to deliver data-driven solutions.

Skills

Python

SQL

Dataiku

Hadoop

Spark

MLFlow

MLOps

Communication

Leadership

Presentation Skills

Education

Master's in Data Science, Statistics, Computer Science or related field

Job description

Job Summary : The Team Lead Data Scientist will oversee the data science team, leading initiatives to develop and implement advanced machine learning models with some of the use cases tailored for the telecommunications sector. This role will ensure the delivery of the data science use cases as per plan with a supporting data stack by closely communicating with the data engineering team through providing end-to-end technical expertise. The role involves collaborating with various departments and stakeholders to leverage data for strategic decision-making.

Key Responsibilities :

1. Lead and mentor a team of data scientists and engineers.

2. Work closely with the data engineering team to design, build, and maintain scalable data pipelines and IT environments for data storage, processing, and retrieval to support data science activities.

3. Lead the data science team to Develop and implement machine learning models for predictive and prescriptive analytics in telecom using tools such as Python, SQL, and Dataiku.

4. Develop and implement data models and architecture to support data use cases.

5. Work closely with the data engineering team to Support extracting, transforming, and loading (ETL) data from various sources into data warehouses, ensuring data quality and integrity to be aware of the complete use case implementation cycle.

6. Work closely with the data engineering team to Optimize data pipelines, queries, and processes to improve performance and efficiency.

7. Identify and resolve data-related issues, providing technical support and ensuring the reliability and availability of data systems.

8. Collaborate with teams, including data scientists, AI, and other stakeholders, to understand data requirements and deliver solutions that meet business needs.

9. Evaluate new technologies and tools, integrating them into existing data infrastructure to enhance capabilities and meet evolving business requirements.

10. Stay updated with the latest developments in data science, techniques, and best practices.

Qualifications :

• Master’s preferred in Data Science, Statistics, Computer Science, or a related field.
• At least 5 years of hands-on experience in data science, with a comprehensive understanding of data management principles.
• Proven track record in architecting and delivering robust data platforms, showcasing expertise in designing scalable and efficient solutions.
• Knowledge of CRISP-DM methodology.

Skills :

• Proficiency in Python, SQL, and Dataiku.
• Strong proficiency with Hadoop and Spark platforms.
• Excellent communication and leadership skills.
• Excellent communication and presentation skills.
• Experience with big data technologies (e.g., Hadoop, Cloudera).
• Familiarity with MLFlow and MLOps

Preferred Qualifications :

• Proficiency or Certification in MLOps and DevOps practices.
• Local GCC experience, preferably Saudi projects.
• Experience in the telecommunications industry.