Data Scientist

V15P1Talonnn; Palo Alto (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

V15P1Talonnn in Palo Alto, CA seeks a Data Scientist to uncover information hidden in large data sets and help drive smarter product decisions. The role focuses on data mining, statistics, and building predictive systems integrated with our products.

You will apply machine learning, feature selection, and data integration techniques while ensuring data quality, and you will collaborate with cross-functional teams to deliver actionable insights and robust analytics solutions that inform product

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

Skills

Feature selection

Machine learning

Statistical analysis

Data cleansing

Anomaly detection

Ad-hoc analysis

Tools

Python

SQL

scikit-learn

TensorFlow

Job description

If you are unable to complete this application due to a disability, contact this employer to ask for an accommodation or an alternative application process.

Data Scientist

Management Palo Alto, CA, US

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