Data Scientist_Oct25

V15P1Talonnn; New York (NY); On-site; USD 100 - 200; Full time

Job summary

V15P1Talonnn in New York, NY, is seeking a Data Scientist to uncover insights from large datasets and drive smarter product decisions. The role focuses on data mining, statistical analysis, and building high-quality predictive systems integrated with our products.

You will select features, extend data with external sources, and improve data collection for analytics, while performing cleansing and validation. Expect hands-on analysis and ongoing anomaly detection with system performance tracking.

Qualifications

• Experience applying data mining techniques and statistical analysis to large datasets.
• Proficiency in machine learning methods and building predictive models.

Responsibilities

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

Skills

Data mining techniques

Statistical analysis

Machine learning

Predictive modeling

Job description

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Data Scientist_Oct25

Management New York City, NY, US

30+ days ago Requisition ID: 5250073

Salary Range: $100.00 To $200.00 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