Salla E-Commerce Platform

Data Scientist

• Architect and implement LLM-based agentic systems including the customer support troubleshooting, analytics, and content-generation tools.**
• Build RAG pipelines combining structured and unstructured sources (knowledge base, FAQs, policies), optimizing for latency, factuality, and grounding.**
• Develop evaluation frameworks (LLM-as-a-judge, human-in-the-loop) to measure helpfulness, factual accuracy, coverage, and coherence.****
• Collaborate with product and UX teams to define prompt hierarchies, tool-calling logic, and conversational workflows that handle multi-turn reasoning.**
• Drive fine-tuning or parameter-efficient adaptation (LoRA, PEFT) of LLMs for commerce-specific reasoning and multilingual support (Arabic & English).**
• Contribute to the GenAI Suite: product description generation, email and blog content creation, landing page design, and brand-aware tone control.**
• Lead experimentation on new LLM orchestration frameworks (LangGraph, semantic routers) and scalable deployment using Bedrock, SageMaker, or Vertex AI.**
• Mentor junior data scientists and define best practices for versioning, prompt evaluation, and observability (e.g., LangFuse, MLflow, Grafana).

Senior Data Scientist – Generative AI

Data Engineer

• Design, implement, maintain and document highly scalable data pipelines for real-time and batch processing.
• Build and optimize data systems to support accurate, low-latency analytics and reporting use cases.
• Develop and maintain solutions for streaming and serverless data processing.
• Collaborate with cross-functional teams to implement and support end-to-end analytics workflows.
• Ensure data quality, reliability, and performance across the platform.
• Monitor, troubleshoot, and optimize data infrastructure to maintain high availability.
• Mentor junior engineers and contribute to the continuous improvement of engineering practices.
• Strong problem-solving skills and the ability to thrive in a fast-paced environment.
• Excellent communication and teamwork skills.

Senior Data Engineer

Product Manager

• Own and drive the multi-quarter roadmap, turning strategy into measurable outcomes.
• Turn uncertainty into direction. Cut through noise, align teams, and focus everyone on what matters most.
• Lead discovery and validation with depth. Stay close to merchants, observe their challenges, and turn insights into action.
• Ship scalable, reliable, merchant-loved products that make a clear difference in growth and efficiency.
• Coach PMs to think sharply, execute with discipline, and stay close to real users and real data.
• Balance speed with precision. Know when to sprint and when to pause to refine and sweat the details.
• Collaborate beyond your scope. Step into challenges that move Salla forward, not just your own roadmap.
• Communicate openly. Explain trade-offs, share reasoning, and bring context to every conversation.

Senior Product Manager

• Analyze raw data: assessing quality, cleansing, preprocessing, structuring for downstream processing.
• Conduct research and development activities, data exploration and discovery using Data Science and Machine Learning (ML) practices.
• Develop, apply, test and implement Data Science and ML models for a wide variety of datasets gathered from different data sources such as Online market places, e-commerce platforms, social media, and web sources.
• Design and develop accurate and scalable ML models in different domains and applications, which include, but not limited to, Recommendation engines, Chatbots, NLP, text mining, text-based feature selection/representation, optimization and predictive modeling.
• Utilize a variety of tools and approaches to solve complex business objectives, from Recommendation Engines, Chatbots, Natural Language Processing (NLP), Machine Learning/ Deep Learning, Image Processing, Speech Processing, Rule-Based Learning and Knowledge Graphs.
• Design new service offerings and solutions in E-Commerce and different fields.
• Keep up to date with latest trends and technologies in the data science and ML fields.
• Work closely with Data Engineers in data related requests, and Data Quality Assurance Officers in data integrity issues.
• Work closely with Business Analysts and product development teams to understand and implement their requirements.
• Collaborate with big data and software developers to translate ideas, models and prototypes into full-fledged solutions.
• Work closely with cross-functional teams to identify challenges and problems and suggest potential AI solutions.

Senior Data Scientist

Analyst

• Monitor and analyze transactions for signs of fraudulent activity.
• Conduct thorough investigations into suspicious transactions and alert relevant departments as necessary.
• Collaborate with various teams to develop resources and tools to mitigate fraud risks.
• Stay informed about the latest trends in fraud detection and prevention.
• Prepare detailed reports on findings, trends, and recommendations for improvement.
• Educate staff and clients on best practices for preventing fraud.
• Assist in the design and implementation of fraud prevention policies.
• Work with law enforcement and regulatory bodies when necessary.
• Exceptional attention to detail and problem-solving abilities.
• High level of integrity and ability to handle sensitive information.

Fraud Analyst

• Define and communicate the product vision and roadmap that aligns with Salla’s business objectives.
• Engage directly with merchants and users to gather insights, identify pain points, and validate new product ideas.”
• Collaborate with design (using Figma) and engineering teams (through Jira) to ensure seamless delivery of features and alignment across all stakeholders..
• Analyze market trends and competitive landscape to inform product strategies.
• Manage the full product lifecycle, from ideation and market validation to launch, measurement, and continuous improvement.
• Define and track key performance indicators (KPIs) for product success.
• Create and maintain detailed product documentation, including requirements specifications and user stories.
• Ensure timely delivery of products and features within budget.
• Foster a culture of innovation and continuous improvement within the product team.

Product Manager – Marketplace

Recruitment

• Lead end-to-end recruitment strategy and full recruitment cycle for technical and non-technical roles.
• Develop and implement talent acquisition strategies to attract top-tier candidates across departments.
• Collaborate with hiring managers to identify staffing needs and create accurate job descriptions.
• Utilize job boards, social media, networking, and other sourcing methods to build candidate pipelines.
• Screen resumes, conduct interviews, evaluate candidates, negotiate offers, and facilitate onboarding.
• Analyze recruitment metrics and continuously improve processes to enhance efficiency and candidate experience.
• Act as employer brand ambassador promoting Salla's mission, values, and a human-centric hiring experience.

Talent Acquisition Lead

• Develop, compile, and oversee a range of reports such as SLA reports, Operational Excellence reports, Graylog reports, and additional performance-related reports.
• Analyze data to identify trends, issues, and areas for improvement.
• Collaborate with different teams to understand their reporting needs and provide data-driven insights.
• Ensure data accuracy and consistency across all reports.
• Utilize data visualization tools to present data in an understandable and actionable manner.
• Support the team with technical issues related to data and the E-commerce platform.
• Maintain and improve reporting processes and tools to enhance efficiency and effectiveness.
• Assist in the implementation of new reporting tools and systems.
• Provide training and support to team members on report generation and data analysis.
• Stay up-to-date with industry best practices and emerging trends in data quality assurance.

Senior Quality and Technical Operations Analyst

Analytics Engineer

• The Senior/Staff Analytics Engineer at Salla will play a critical role in harnessing data to drive strategic business decisions. This position involves developing and maintaining robust data pipelines, creating insightful analytics solutions, and collaborating with cross-functional teams to elevate data literacy.
• As a senior member of the team, you will lead initiatives to improve our analytics infrastructure, ensuring that business units have access to high-quality data for analysis and reporting.
• Design, develop, and maintain scalable data models and transformation pipelines (dbt, SQL, Databricks/BigQuery/Snowflake).
• Partner with business, product, and analytics teams to align data products with strategic KPIs (e-commerce, merchant success, customer experience).
• Establish and enforce data governance, testing, documentation, and quality standards across the stack.
• Orchestrate workflows with Airflow (or equivalent) to ensure automation, traceability, and reliability.
• Collaborate with engineers to integrate upstream data sources (APIs, event pipelines, real-time and batch data).
• Improve developer and analyst experience through semantic layer design, self-service enablement, and performance optimization.
• Mentor junior engineers and contribute to the maturity of Salla’s data organization.

Senior/Staff Analytics Engineer

Product Designer

• Salla is excited to announce an opening for a UI Designer under the Tamheer program.
• This role is designed for recent graduates who are looking to gain hands-on experience in UI design. As a UI Designer, you will assist in creating user-centric interfaces that not only look great but also provide a seamless user experience.
• You will work closely with experienced designers and development teams to learn the ropes of the design process, from conceptualization to execution.
• Join us to kickstart your career and contribute to innovative design projects that shape the future of Salla!
• Responsibilities:
• Assist in gathering user requirements and translating them into design concepts.
• Create wireframes, prototypes, and visual designs under the guidance of senior designers.
• Participate in brainstorming sessions to propose creative design solutions.
• Support user testing activities to gather feedback and iterate on designs.
• Stay updated with design trends and integrate best practices into your work.

UI Designer

Engineering Manager

As the Head of Engineering for our Payment/Fintech division, you will oversee the development and optimization of our payment processing systems, including fraud detection, payout systems, and improving payment acceptance rates. You will lead the engineering team, set strategic technical direction, and collaborate with other departments to ensure the platform is secure, scalable, and efficient. Your experience in payment systems, fraud detection, and systems monitoring will be critical in safeguarding transactions and maintaining optimal platform performance.

Key Responsibilities

Supervisory & Leadership Responsibilities:
Engineering Standards & Practices: Establish high engineering standards for the development of secure, scalable, and efficient payment and fraud detection systems, ensuring compliance with industry regulations.
Team Leadership & Mentorship: Lead and mentor cross-functional engineering teams (including back-end, front-end, QA) with a focus on professional development, fostering innovation and ownership.
Cross-Functional Collaboration: Collaborate with Product, Compliance, Risk, and Finance teams to ensure payment systems, fraud detection protocols, and monitoring tools are aligned with business needs and regulatory standards.
Hiring & Team Development: Recruit, develop, and retain top talent in payment and fintech engineering, fostering a culture of continuous learning and professional growth.

Strategic Responsibilities:
Payment Infrastructure Strategy: Lead the development of the payment platform's architecture, focusing on improving transaction performance, scaling systems for growth, and reducing downtime.
Fraud Detection & Prevention: Develop, use, and implement advanced fraud detection rules and machine learning models to detect suspicious activities in real-time, ensuring compliance with KYC, AML, and regulatory standards.
Project & Resource Management: Oversee the planning, development, and execution of payment and fraud detection features, ensuring projects are delivered on time, within scope, and within budget.
Payout Systems: Manage the development and optimization of payout systems, ensuring smooth and timely payments to merchants and stakeholders.
Risk Management & Security: Ensure robust security measures are implemented to protect sensitive payment data, working with compliance teams to maintain adherence to standards such as PCI-DSS and GDPR.

Industry Knowledge:
Payment Processing Expertise: Lead the development and optimization of the payment processing system, reducing transaction failures and improving acceptance rates through smart routing, tokenization, and payment gateway integrations.
Fraud Detection Rules: Implement and refine fraud detection rules that adapt to changing fraud patterns, leveraging machine learning and analytics to minimize false positives and enhance real-time threat detection.
Payment Gateway Integration: Oversee the integration of multiple payment gateways, optimizing transaction routing and redundancy to ensure seamless processing.
Acceptance Rate Enhancement: Use data and analysis to identify and implement strategies for increasing payment acceptance rates, reducing transaction declines, and improving customer satisfaction.
Technical & Knowledge Responsibilities:
Systems Monitoring & Performance Management: Establish advanced monitoring systems for real-time tracking of payment transactions, fraud detection activities, system health, and performance metrics. Ensure prompt issue resolution and minimal system downtime.
Security & Compliance: Ensure the platform complies with regulatory standards, focusing on fraud detection, anti-money laundering (AML), and Know Your Customer (KYC) regulations. Collaborate with legal and compliance teams to maintain certifications like PCI-DSS.
Data-Driven Decision Making: Leverage analytics and machine learning to monitor and predict system performance, fraud activities, and payment failures. Use data insights to continuously optimize the platform.