Data Scientist

V15P1Talonnn; New York (NY); On-site; USD 150,000 - 200,000; Full time

Job summary

V15P1Talonnn in New York, NY is seeking a Data Scientist to uncover information in vast data sets and enable smarter product decisions. You will apply data mining techniques, perform statistical analyses, and build high-quality prediction systems integrated with our products.

The role focuses on feature selection, model development, and expanding data sources, with rigorous data cleaning and anomaly detection to track performance over time.

Qualifications

• Experience applying data mining and ML techniques to large datasets.
• Proficiency in statistical analysis and modeling.
• Ability to build predictive systems integrated with products.

Responsibilities

• Selecting features and building classifiers using machine learning techniques.
• Extending company’s data with third party sources when needed.
• Enhancing data collection procedures for analytic systems.
• Processing, cleansing, and verifying data integrity for analysis.
• Doing ad-hoc analysis and presenting results clearly.
• Creating automated anomaly detection systems and monitoring performance.

Skills

Data mining

Statistical analysis

Machine learning

Predictive modeling

Job description

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Data Scientist

Management New York, NY, US

30+ days ago Requisition ID: 5250413

Salary Range: $150,000.00 To $200,000.00 Annually

We are looking for a data scientist that will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products.

Responsibilities

• Selecting features, building and optimizing classifiers using machine learning techniques
• Extending company’s data with third party sources of information when needed
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance