About Me

Sitraka Forler

Hello! I'm Sitraka FORLER, a French Data & IT professional passionate about building intelligent systems that create real-world impact. With expertise spanning Data Science, Machine Learning, Cloud, and Cybersecurity, I help organizations unlock the value hidden in their data.

Alongside my consulting career, I am the Co-Founder of LuxAiOps, a startup dedicated to bringing intelligent IT Operations and automation to Luxembourg and Europe. I also take on freelance projects — delivering tailored, production-ready solutions to clients.

Feel free to explore my professional experience, browse my technical skills, learn about LuxAiOps, or get in touch. You can also visit my main website at sitraka.fr.

Experience

Engineering
June 2025 — Present | Luxembourg

☁️ Systems Architect & Ai Ops

POST Luxembourg
  • Designing and leading AIOps architecture to bridge observability, automation, and data-driven decision-making.
  • Evolving observability architecture leveraging Splunk, Zabbix, Grafana, Prometheus, and ELK.
  • Modeling business and technical services in BMC Discovery (CMDB).
  • Automating incident response workflows with ServiceNow and intelligent alerting.
  • Driving AIOps strategy using machine learning and anomaly detection.
March 2023 — Present | France & Luxembourg

🎓 Visiting Professor & Lecturer

IAE Metz, Centrale Méditerranée & AMSE
  • Teaching Data Science for Finance, Machine Learning, Deep Learning, and Transformers.
  • Lecturing on corporate strategy, Agile/Scrum, and corporate finance.
October 2023 — June 2025 | Luxembourg

🧠 Senior Data Scientist

REVEALS SA
  • Designing and deploying LLMs from POC to Production.
  • Managing Data Engineering and Architecture for finance departments.
  • Executing large-scale data migration projects.
Sept 2022 — Oct 2023 | Luxembourg

🏢 Consultant in Data & Digital Transformation

Square Management
  • Automated workflows with RPA (Python) for Avaloq core-banking.
  • Designed data warehouses using AWS, Airflow, and Talend.
  • Automated financial/regulatory reporting (AIFM, FGDL, IFRS 9).
March 2021 — Sept 2022 | France

📊 Data Scientist / Web Analyst

VirtualExpo Group
  • Applied NLP (Hugging Face, Keras) to product descriptions.
  • Built predictive models and web traffic KPI dashboards.

Code & Skills

Code

🚀 Tech Stack

Python & ML
Deep Learning
Cloud Architect
SQL & NoSQL
Cybersecurity
FinTech

💻 Data Science & Analytics

I drive the development and production of ML models in asset management, automation, and data insights. The goal is always: does it bring value to the customer? Does it bring value to the planet? 🌍

🔐 Cybersecurity & Monitoring

Hands-on experience with Venafi (certificate management) and Splunk (advanced SIEM analytics) — ensuring data security, anomaly detection, and system integrity.

🗄️ Databases

Relational (MySQL, PostgreSQL) and NoSQL (MongoDB, Cassandra). Key competencies:

  • Entity-Relationship modeling & normalization
  • Complex SQL queries (JOINs, aggregations, CTEs)
  • Indexing strategies & query optimization
  • ACID properties & transaction management

Example SQL query:

SELECT customer_id, SUM(amount) AS total_amount
FROM transactions
WHERE transaction_date >= '2023-01-01'
GROUP BY customer_id
HAVING SUM(amount) > 1000
ORDER BY total_amount DESC;

📈 Data in Finance

From risk modeling to algorithmic trading — I leverage data to power financial insights.

  • Time series analysis for market prediction
  • Risk modeling with statistical methods
  • High-frequency trading data processing
  • Regulatory compliance & data governance

Interactive Compound Interest Calculator

Try it out with different values:

🐍 Python Code Examples

Stock data analysis with pandas:

import pandas as pd
import numpy as np

df = pd.read_csv('stock_data.csv', parse_dates=['Date'], index_col='Date')
df['Daily_Return'] = df['Close'].pct_change()
volatility = df['Daily_Return'].std() * np.sqrt(252)
df['MA_50'] = df['Close'].rolling(window=50).mean()

print(f"Annualized Volatility: {volatility:.2%}")
print(df.tail())

Compound interest function:

def compound_interest(principal, rate, time, n=1):
    amount = principal * (1 + rate/n) ** (n * time)
    return amount, amount - principal

final, earned = compound_interest(1000, 0.05, 5)
print(f"Final: ${final:.2f}  |  Interest: ${earned:.2f}")

LuxAiOps

LuxAiOps

Pioneering AIOps (Artificial Intelligence for IT Operations) in Luxembourg and across Europe.

🚀 Our Vision

Modern IT infrastructure is becoming increasingly complex. At LuxAiOps, we believe the solution is leveraging AI/ML to automate monitoring, detect anomalies before they cause downtime, and streamline IT operations. We are building the next generation of intelligent tools for enterprise resilience.

🛠️ Core Offerings

  • Predictive Analytics: Forecasting system failures and resource bottlenecks before they impact the business.
  • Intelligent Automation: Automated root-cause analysis and self-healing systems.
  • Secure & Compliant AI: Solutions tailored to the strict regulatory requirements of the European market (GDPR, DORA).
  • MLOps Consulting: Helping companies deploy and scale their own machine learning models reliably.