Data Scientist (Remote)

• Selecting features, building and optimizing classifiers using machine learning techniques
• Data mining using state of the art methods
• Extending business 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 performanceSkills and Qualifications

• Min 8 yrs of experience
• Hands on experience in Python
• Excellent understanding of machine learning techniques and algorithms.
• Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, etc Excellence in at least one of these is highly desirable
• Great communication skills
• Experience with data visualization tools, such as GGplot, etc.
• Proficiency in using query languages such as SQL, Hive, Pig
• Experience with NoSQL databases, such as MongoDB
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills
• Data oriented personality

Job Types: Full-time, Contract

Salary: $70,000.00 to $120,000.00 /year

Experience:

• relevant: 3 years (Required)

Education:

• Bachelor's (Required)

Work authorization:

• United States (Required)

Contract Length:

• More than 1 year
• Varies

Contract Renewal:

• Likely

Additional Compensation:

• Bonuses

Work Location:

• Multiple locations
• Fully Remote
• One location

This Company Describes Its Culture as:

• Team-oriented -- cooperative and collaborative
• People-oriented -- supportive and fairness-focused
• Stable -- traditional, stable, strong processes
• Outcome-oriented -- results-focused with strong performance culture
• Aggressive -- competitive and growth-oriented
• Innovative -- innovative and risk-taking
• Detail-oriented -- quality and precision-focused

Schedule::

• Monday to Friday