Team Lead Data Science

2 weeks ago

Centurion, Gauteng, South Africa Tracker South Africa Full time

Listing reference:
track_001163

Listing status:
Online

Position summary:

Industry:
IT & Internet
Job category:Others: IT and Telecommunication
Location:Centurion
Contract:Permanent
Remuneration:Market Related
EE position:Yes
Introduction:

Tracker is looking for a talented and driven Team Lead Data Science to lead our data science team and help us deliver innovative solutions using AI, data science and machine learning.

As a Team Lead Data Science, you will be responsible for managing the team, overseeing the projects, ensuring high-quality standards, and collaborating with other teams and stakeholders.

You will also be directly involved in developing and deploying AI solutions, the latter being a highly desirable skill for this role.

To be successful in this role, you should have at least 1 year of experience as a team lead directly following 2 years of experience as a senior data scientist or senior developer in data science and machine learning projects.

You should also have strong technical skills in AI, Python, DataBricks, PySpark, Azure, SQL, PowerBI, GIS, Linux, and other programming languages like Java and/or C#.

Previous experience in AIOps, MLOps, LLMs, telemetry, IoT, or Engineering domains is a plus.

Job description:

KEY DUTIES AND RESPONSIBILITES:

-
Leadership
- o Collaborate closely with the data science manager to establish and execute the team's technical vision, strategy, and goals.
- o Provide effective leadership to the data science team, fostering a collaborative and innovative environment that encourages creativity and growth.
- o Guide and mentor team members, promoting their professional development and enhancing their skills in AI, data science, machine learning, and related technologies.
- o Effectively manage and allocate resources, ensuring efficient project execution, and alignment with business goals.
- o Continuously align delivery to the Tracker and Development & Engineering team strategy and planning.
-
Delivery of AI and Data Science solutions
- o Lead and contribute to the end-to-end development of AI solutions using data science and machine learning, ensuring they address real-world challenges in telemetry, IoT, and Engineering domains, as determined by business.
- o Ensure delivery of solutions on time, in budget, with the desired functionality, at the defined quality level in a sustainable way.
- o Collaborate closely with cross-functional teams to gather requirements, design solutions, and integrate insights into operational processes.
- o In collaboration with field experts, coordinate the design and implementation of generative models, contributing to enhanced vehicle tracking, recovery operations, and operational efficiency.
-
Best practice quality and testing
- o Uphold the highest standards of quality in AI and Data Science solutions by implementing best practices in data preparation, model development, validation, data quality, etc.
- o Oversee rigorous testing methodologies to validate the accuracy, reliability, and effectiveness of developed models, ensuring they meet business requirements.
-
System maintenance and support
- o Take responsibility for the ongoing maintenance and optimization of AI / DS products, services, models, and solutions, ensuring they remain effective and aligned with changing business needs.
- o Collaborate with the IT and other engineering teams to address any technical issues, ensure system stability, and provide timely support when required.
-
Knowledge transfer
- o Foster a culture of knowledge sharing within the team by promoting the exchange of expertise, insights, and lessons learned from past projects.
- o Facilitate the documentation of project details, methodologies, and best practices, ensuring seamless knowledge transfer among team members.
- o Mentor and coach junior data science members.
-
Engineering processes and environment
- o Drive the integration of AI solutions into the overall engineering environment, leveraging tools and processes that align with industry best practices.
- o Collaborate with engineers, data engineers, and IT specialists to ensure the scalability, reliability, and security of AI solutions in a production environment.
- o Strive to enhance engineering processes and practices by contributing insights from AI projects to improve the overall operational efficiency of the organization.
- o Effective use of AI and Data Science development toolsets.
- o Follow department development standards as adapted to Data Science.

Minimum requirements:

-
Education:

- o BSc (Comp Sci) (completed) or BEng (completed) or higher qualification of relevance.
- o Other STEM degrees from established Universities (Computers, Math, Stats, IT or BCom-IT) might be considered given relevant minimum experience.
- o Additional leadership development an advantage.
-


Working Experience:

Minimum 4 years hands-on experience:

  • Minimum of 4 years of rel

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