Data Scientist

Key Responsibilities

• Develop and optimize machine learning and statistical models for anomaly detection, predictive analytics, and process optimization.
• Perform advanced data analysis, visualization, Bayesian modeling, and Monte Carlo simulations.
• Implement real-time monitoring solutions for data streams and system performance.
• Analyze large and complex datasets to identify trends, anomalies, and root causes.
• Improve alert accuracy and reduce false positives through model tuning and threshold optimization.
• Collaborate with cross‑functional teams including product management, engineering, manufacturing, and IT to deliver scalable data solutions.
• Apply data science and software engineering best practices for robust and reproducible model deployment.
• Support data quality, security, and automated analytics pipelines.
• Research and integrate emerging AI/Generative AI capabilities to improve operational efficiency and experimentation.
• Communicate technical findings and recommendations to both technical and non‑technical stakeholders.

• Strong expertise in Python and data science libraries such as Pandas, scikit‑learn, and Jupyter.
• Experience with machine learning, statistical modeling, optimization techniques, and feature engineering.
• Knowledge of data mining, anomaly detection, and predictive analytics.
• Experience working with large and unstructured datasets.
• Familiarity with AWS, Docker, Git, and software development best practices.
• Working knowledge of relational databases such as PostgreSQL.
• Strong analytical, problem‑solving, and communication skills.
• Ability to manage multiple projects in a fast‑paced environment.