Data Scientist Intern
- 0-1 Years
- Hyderabad | Full-Time Internship | Stipend - Performance-Based | Work from Office
- Sep 27,2022 14:35:31
- Job Title: Data Scientist Intern
- Position Type: FullTime
- Experience: 0 - 1 Years
- Location Hyderabad | Full-Time Internship | Stipend - Performance-Based | Work from Office
- Job Status Active
- As a Data Scientist Intern, you will be responsible for compiling actionable insights from data and assisting program, sales, and marketing managers build data-driven processes. Your role will involve driving initiatives to optimize for operational excellence and revenue.
Ensure that data flows smoothly from source to destination so that it can be processed
Utilize strong database skills to work with large, complex data sets to extract insights
Filter and cleanse unstructured (or ambiguous) data into usable data sets that can be analyzed to extract insights and improve business processes
Identify new internal and external data sources to support analytics initiatives and work with appropriate partners to absorb the data into new or existing data infrastructure
Build tools for automating repetitive tasks so that bandwidth can be freed for analytics
Collaborate with program managers and business analysts to help them come up with actionable, high-impact insights across product lines and functions
Work closely with top management to prioritize information and analytic needs
Bachelors or Masters (Pursuing or Graduated) in a quantitative field (such as Engineering, Statistics, Math, Economics, or Computer Science with Modeling/Data Science), preferably with work experience of over [X] years.
The ability to program in any high-level language is required. Familiarity with R and statistical packages is preferred.
Proven problem-solving and debugging skills.
Familiar with database technologies and tools (SQL/R/SAS/JMP etc.), data warehousing, transformation, and processing. Work experience with real data for customer insights, business, and market analysis will be advantageous.
Experience with text analytics, data mining, and social media analytics.
Statistical knowledge in standard techniques: Logistic Regression, Classification models, Cluster Analysis, Neural Networks, Random Forests, Ensembles, etc.