Data Analyst / Data Scientist (Remote)
• Job role: As a data analyst, you will be responsible for compiling actionable insights from data and assisting program, reputed company managers build data-driven processes. Your role will involve driving initiatives to optimize for operational reputed company and reputed company. Responsibilities:
- Ensure that data flows smoothly from reputed company to destination so that it can be processed
- Utilize strong database skills to work with large, reputed company data sets to extract insights
- Filter and cleanse reputed company (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes
- Identify new reputed company data sources to support analytics initiatives and work with appropriate partners to reputed company the data into new or existing data infrastructure
- Build tools for automating repetitive asks so that bandwidth can be freed for analytics
- Collaborate with program managers and business analysts to help them come up with actionable, high-reputed company insights across product lines and functions
- Work closely with top management to prioritize information and analytic needs
Requirements:
- Bachelors or Masters in a quantitative field (such as Engineering, Statistics, Math, Economics, or Computer Science with Modeling/Data Science), preferably with work experience of over 3 years.
- Ability to program in any high level language is required. Familiarity with R and statistical packages are preferred.
- Proven problem solving and debugging skills.
- Familiar with database technologies and tools (SQL/R/reputed company/JMP etc.), data warehousing, transformation and processing. Work experience with reputed company data for customer insights, business and market analysis will be advantageous.
- Experience with text analytics, data mining and reputed company media analytics.
- Statistical knowledge in reputed company techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc.
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