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Senior Data Scientist
South Africa, South Africa
Actively hiring, first seen by us today- Pay
- Pay not listed
- Work setting
Remote — work setting source
This is a hands-on role for someone who is highly independent and ownership-driven: you’ll define problems, drive execution, and deliver production-grade GenAI capabilities end-to-end. You combine strong software engineering with practical GenAI experience, rigorous evaluation habits, and a bias for shipping improvements that customers feel. Location: Full-time, fully remote. This role is especially well-suited for candidates based in South Africa, with a team culture that supports async collaboration and healthy time-zone overlap. Key Responsibilities:
Work setup in the employer’s posting: TELECOMMUTE
From the employer’s posting- Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingDesign, build, and ship Generative AI capabilities that power tools for technical Q&A and data understanding.
Develop agentic workflows (planning, tool use, retrieval, execution, verification) with measurable quality, reliability, and cost controls.
Build evaluation systems for GenAI: offline test sets, automated scoring, human review loops, regression suites, and production monitoring.
From the employer’s posting
Key Responsibilities: Design, build, and ship Generative AI capabilities that power tools for technical Q&A and data understanding. Develop agentic workflows (planning, tool use, retrieval, execution, verification) with measurable quality, reliability, and cost controls.
Design, build, and ship Generative AI capabilities that power tools for technical Q&A and data understanding. Develop agentic workflows (planning, tool use, retrieval, execution, verification) with measurable quality, reliability, and cost controls. Build evaluation systems for GenAI: offline test sets, automated scoring, human review loops, regression suites, and production monitoring.
Develop agentic workflows (planning, tool use, retrieval, execution, verification) with measurable quality, reliability, and cost controls. Build evaluation systems for GenAI: offline test sets, automated scoring, human review loops, regression suites, and production monitoring. Deliver production-ready services and pipelines (APIs, background jobs, data processing, configuration, release workflows) with strong engineering discipline.
What you’ll bring
All qualificationsCore experience
- 4–8+ years of relevant experience in applied data science and Generative AI/LLM product development, including significant responsibility for production delivery.
- Proven experience delivering GenAI/LLM applications into production (not just prototypes), including reliability and operational considerations.
- Hands-on experience building agents and using agent frameworks (e.g., LangChain, Agno, or similar tool-using agent stacks).
Preferred experience
- Experience with fleet management, telematics, IoT, time-series data, or analytics platforms.
- Experience deploying LLM/GenAI services in cloud environments (Azure/AWS/GCP), including monitoring and cost management.
- Familiarity with security, privacy, and compliance considerations for enterprise AI products.
- Experience building structured LLM evaluations (golden sets, adversarial testing, prompt/agent regression).
Qualification wording
4–8+ years of relevant experience in applied data science and Generative AI/LLM product development, including significant responsibility for production delivery.
Proven experience delivering GenAI/LLM applications into production (not just prototypes), including reliability and operational considerations.
Hands-on experience building agents and using agent frameworks (e.g., LangChain, Agno, or similar tool-using agent stacks).
Experience with fleet management, telematics, IoT, time-series data, or analytics platforms.
Experience deploying LLM/GenAI services in cloud environments (Azure/AWS/GCP), including monitoring and cost management.
Familiarity with security, privacy, and compliance considerations for enterprise AI products.
Experience building structured LLM evaluations (golden sets, adversarial testing, prompt/agent regression).
Posting record
Report an errorActively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 9, 2026today
- Recorded sightings
- 1
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Powerfleet is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring is picking up
See how this role fits your experience
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- Python
- AWS
- Azure
- GCP
Where the posting names them
- 4–8+ years of relevant experience in applied data science and Generative AI/LLM product development, including significant responsibility for production delivery. - Strong programming skills in Python, with modern engineering practices (testing, packaging, CI/CD, APIs, code reviews). - Proven experience delivering GenAI/LLM applications into production (not just prototypes), including reliability and operational considerations.
- Experience with fleet management, telematics, IoT, time-series data, or analytics platforms. - Experience deploying LLM/GenAI services in cloud environments (Azure/AWS/GCP), including monitoring and cost management. - Familiarity with security, privacy, and compliance considerations for enterprise AI products.
Your next step
Complete your application on careers.powerfleet.com. The employer’s form will show what is required.
Already applied? Track this application
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About Powerfleet
Powerfleet (Nasdaq: AIOT; JSE: PWR) is a global leader in the artificial intelligence of things (AIoT) software-as-a-service (SaaS) mobile asset industry. With more than 30 years of experience, Powerfleet unifies business operations through the ingestion, harmonisation, and integration of data—regardless of source—and delivers actionable insights to help companies meet their strategic objectives around Safety, Compliance, Efficiency and Sustainability. Our people-first culture and relentless innovation empower customers to achieve measurable, sustainable business improvements. Powerfleet serves over 2.6 million subscribers across more than 48,000 customers in 120 countries, with commercial operations across every major continent.
Job Overview
Powerfleet is looking for a Data Scientist to join our AI Team and help build tools that enable customers to answer technical questions, troubleshoot issues, and understand their fleet and asset data.
This is a hands-on role for someone who is highly independent and ownership-driven: you’ll define problems, drive execution, and deliver production-grade GenAI capabilities end-to-end. You combine strong software engineering with practical GenAI experience, rigorous evaluation habits, and a bias for shipping improvements that customers feel.
Location: Full-time, fully remote. This role is especially well-suited for candidates based in South Africa, with a team culture that supports async collaboration and healthy time-zone overlap.
Key Responsibilities:
Design, build, and ship Generative AI capabilities that power tools for technical Q&A and data understanding.
Develop agentic workflows (planning, tool use, retrieval, execution, verification) with measurable quality, reliability, and cost controls.
Build evaluation systems for GenAI: offline test sets, automated scoring, human review loops, regression suites, and production monitoring.
Deliver production-ready services and pipelines (APIs, background jobs, data processing, configuration, release workflows) with strong engineering discipline.
Partner with product, engineering, and domain experts to translate customer problems into milestones, acceptance criteria, and clear success metrics.
Improve system quality through testing, observability, performance optimization (latency and scalability), and guardrails.
Contribute to an engineering-first culture: thoughtful design docs, code reviews, and pragmatic technical decisions.
Qualifications:
4–8+ years of relevant experience in applied data science and Generative AI/LLM product development, including significant responsibility for production delivery.
Strong programming skills in Python, with modern engineering practices (testing, packaging, CI/CD, APIs, code reviews).
Proven experience delivering GenAI/LLM applications into production (not just prototypes), including reliability and operational considerations.
Hands-on experience building agents and using agent frameworks (e.g., LangChain, Agno, or similar tool-using agent stacks).
Delivery-oriented and comfortable owning ambiguous problems end-to-end: scoping, implementation, rollout, and iteration.
Independent, autonomous, self-driven, and proactive in a remote team; able to take a problem area and drive it to outcomes with minimal oversight.
Clear communicator: able to explain trade-offs, write crisp documentation, and align stakeholders.
Deeply curious and committed to staying up to date with the latest developments in Generative AI and agent frameworks, recognizing the field evolves rapidly.
Preferred Qualifications:
Experience with fleet management, telematics, IoT, time-series data, or analytics platforms.
Experience deploying LLM/GenAI services in cloud environments (Azure/AWS/GCP), including monitoring and cost management.
Familiarity with security, privacy, and compliance considerations for enterprise AI products.
Experience building structured LLM evaluations (golden sets, adversarial testing, prompt/agent regression).
Exposure to multi-region or multi-language product needs.
Benefits:
Fully remote role with a remote-first team culture (well-suited to Europe and South Africa time zones).
High-ownership work on a customer-facing AI product that solves real operational and technical problems.
Environment that values shipping, measurable impact, and maintainable systems.
Competitive, region-aligned compensation and meaningful opportunities to grow scope based on impact.
If you’re excited by building reliable, production-grade AI assistants—and you bring strong engineering plus applied GenAI expertise—we’d love to hear from you.
EEO/ BEE Statement
Powerfleet is an equal opportunity employer committed to employment equity, diversity, and inclusion. In alignment with the Employment Equity Act 1998 and our Employment Equity plan, we actively encourage applications from designated groups, including Black people, women, and individuals with disabilities.
As part of our commitment to transformation and in accordance with the Broad-Based Black Economic Empowerment Act, preference may be given to candidates from designated groups where appropriate. All qualified applicants will be considered based on merit, skills, and experience.
We are committed to providing reasonable accommodation throughout the recruitment process. If you require support or adjustments, please let us know.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
South Africa, South Africa
This is a hands-on role for someone who is highly independent and ownership-driven: you’ll define problems, drive execution, and deliver production-grade GenAI capabilities end-to-end. You combine strong software engineering with practical GenAI experience, rigorous evaluation habits, and a bias for shipping improvements that customers feel. Location: Full-time, fully remote. This role is especially well-suited for candidates based in South Africa, with a team culture that supports async collaboration and healthy time-zone overlap. Key Responsibilities:
More source context
- Delivery-oriented and comfortable owning ambiguous problems end-to-end: scoping, implementation, rollout, and iteration. - Independent, autonomous, self-driven, and proactive in a remote team; able to take a problem area and drive it to outcomes with minimal oversight. - Clear communicator: able to explain trade-offs, write crisp documentation, and align stakeholders.
More relevant text appears in the full description.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.