Advanced Data Scientist

You will be part of a strategic initiative focused on developing predictive maintenance algorithms for manufacturing operations. The solution aims to detect equipment issues before failures occur, improving uptime and reducing costs.

Built on advanced data science and MLOps practices, the platform will deliver actionable insights fully integrated into existing engineering workflows.

Key Responsibilities:

• Drive the development of pipelines for transforming raw sensor data using time-windowing, FFT, and domain-specific features.
• Design and implement anomaly and failure detection models, both unsupervised and supervised, ensuring robust and compliant architectures.
• Collaborate across roles to align on requirements and delivery plans, supporting RUL forecasting with time-series models like LSTM.
• Apply explainable AI tools and create diagnostic visualizations to build trust and transparency, maintaining strong experiment tracking and versioning.
• Mentor and support team members through the ML lifecycle, securing deployments and monitoring.

Required Skills:

• 4+ years of experience with Python and its data science ecosystem (Pandas, NumPy, Scikit-learn).
• Proficiency in advanced feature engineering techniques, including transformation of raw sensor data into meaningful features for machine learning models.
• Hands-on experience with unsupervised anomaly detection algorithms and supervised machine learning models, including Random Forest and XGBoost.
• Good understanding of explainable AI frameworks and MLOps practices.

Benefits:

• We offer a holistic benefits program covering social, physical, emotional wellbeing, and work-life fusion.
• Enjoy our wellbeing program, including medical benefits, gym support, and personalized fitness options.
• We believe in investing in our mental wellbeing just as much as our physical health, social connections, or work-life balance.