EI
Data Scientist
Expert In Recruitment Solutions
🇺🇸 United States
Remote
4 months ago
- Bayesian
- Machine Learning
- Python
- Jupyter
- Pandas
- scikit-learn
- AWS
- Docker
- Git
- PostgreSQL
4 months ago
· Support a wide variety of analytical, quality control, and manufacturing processes through advanced data analysis and visualization, statistical modeling, and Bayesian experimental design
· Apply advanced techniques such as constrained optimization, machine learning, and Monte Carlo simulations to solve complex challenges including schedule optimization and batch generation
· Identify high-impact opportunities by leveraging and applying the latest advances in computer science and operations research, continuously staying at the forefront of the field
· Partner closely with cross-functional business and product stakeholders to iteratively align on project goals across the full lifecycle—spanning data acquisition, modeling strategy, validation, deployment, and monitoring
· Collaborate deeply with data scientists, engineers, research scientists, statisticians, and manufacturing teams to drive integrated, scalable solutions
· Champion and implement data science and software engineering best practices to ensure robustness, reproducibility, and scalability of solutions
· Communicate complex analytical findings clearly and effectively to both technical and non-technical audiences, internally and externally
· Explore and integrate emerging Generative AI capabilities to enhance modeling approaches, accelerate experimentation, and unlock new efficiencies across manufacturing and development workflows
Here's What You'll Need (Basic Qualifications)
· Ph.D. in a quantitative STEM field (technology, engineering, and mathematics) with 0-2 years of professional experience, or a Master's degree plus
· 5-8 years of relevant professional experience required.
· Experience with optimization (combinatorial, discrete, convex, etc.) preferred but not required.
· Background in bioinformatics preferred but not required.
· Experience delivering data science projects analyzing and modeling scientific engineering data, preferably in an industry setting.
· Outstanding communication skills (verbal, written and remote).
· Demonstrated experience in collecting, cleaning, and analyzing large and/or unstructured datasets and effectively communicating insights.
· Fluency in Python, especially the data scientific stack (Jupyter/Pandas/scikit-learn) and machine learning libraries
· Familiarity with best practices in software development, including Amazon Web Services, Docker, version control (Git), and documentation.
· Working knowledge of relational databases (e.g., PostgreSQL).
· Ability to manage multiple projects and effectively collaborate in a dynamic, cross-functional environment.
· Proficiency in English (verbal and/or written) required due to global collaboration needs
Key Responsibilities
- Model Development: Design, train, and tune machine learning models (unsupervised/supervised) and statistical algorithms to detect anomalies.
- System Monitoring: Implement real-time monitoring of data streams and system logs to identify deviations from expected behavior.
- Data Analysis & Investigation: Analyze large, complex datasets to investigate root causes of flagged anomalies.
- Alert Optimization: Reduce false positives by tuning detection thresholds, ensuring high-accuracy alerts.
- Collaboration: Work with product management, data engineers and IT teams to implement data quality, security, and automated detection pipelines
- Data Techniques: Strong understanding of statistical analysis, data mining, and feature engineering.
Data Scientist · Expert In Recruitment Solutions