Über Saad Ahmed
I’m a Senior Data Scientist with 10+ years of experience building data-driven solutions across retail, telecom, and fintech.
My expertise spans end-to-end data workflows—from ETL pipeline design and data modeling to machine learning, optimization, and deployment. I have hands-on experience working with scalable solutions for pricing, demand forecasting, and customer analytics.
Recently, I’ve also been working with Large Language Models (LLMs), integrating them into real-world applications such as intelligent automation, text analysis, and AI-powered decision support systems.
What I can help you with:
Predictive Analytics, ETL pipelines, and data engineering
Machine learning models (forecasting, optimization, classification)
Pricing and revenue optimization solutions
LLM-powered applications (chatbots, text processing, AI integrations)
Dashboarding and reporting (Looker, etc.)
I focus on delivering solutions that are not just technically sound, but also aligned with business goals and easy to integrate into existing systems.
Let’s work together to turn your data into a competitive advantage.
Englisch
Muttersprachlich oder zweisprachig
Deutsch
Konversationssicher
Vor Ort möglich
Berlin (bis zu 50 km)
Projekt- und Berufserfahrung
- Centric SoftwareSenior Data Scientist - Product Lifecycle PricingJanuar 2024 - Heute (2 Jahre und 5 Monate)Berlin, Deutschland• - Delivered demand forecasting models for B2B retail clients, enabling more accurate pricing and inventory planning across product lifecycles.• - Implemented markdown optimization algorithms that improved sell-through rates and increased revenue recovery on end-of-season inventory.• - Leveraged historical discount and promotion data to enhance promotion optimization strategies, helping retailers improve pricing effectiveness and promotional ROI.
- Ratepay GmbHData Scientist - Risk ManagementBANKEN & VERSICHERUNGENJanuar 2022 - Januar 2024 (2 Jahre)Berlin, Deutschland• - Optimized machine learning models to catch fraudulent transactions by introducing new features and segmentation techniques• - Scaled the fraud prediction model by introducing a generic model that could run for transactions from multiple shops, which is expected to saved 400k euros in fraud volume for clients like Zara, Paypal and Shop Apotheke• - Introduced in house Credit Risk Model that saved the company 200k euros per month which was otherwise lost to credit default
- Zalando SESoftware EngineerGROSSHANDELJanuar 2019 - Januar 2022 (3 Jahre)Berlin, Deutschland• - Automated bid steering process for Zalando on X(previously known as twitter) and google Ads• - Facilitated strategic decision making for personalized marketing via Data Analytics• - Developed Datamarts for reporting on digital campaigns performance on metrics such as ClickRate, Impressions, Conversion Rates which helped generate dashboards for market managers to navigate the steering process
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Ausbildung und Abschlüsse
- Statistical InferenceJohn HopkinsUniversity2018Statistical Inference
- Deep Learning and Reinforcement LearningIBM2021Deep Learning and Reinforcement Learning