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.

Required Skills

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.