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Data Scientist
Data Scientist
Networth Corp is seeking an Entry-Level Data Scientist to implement data transformation and data science integration using Python-based pipelines and cloud services. Key responsibilities include data extraction, transformation, feature engineering, and algorithm development to generate actionable business insights.
About the role
Description
- We are looking for 2018 and later graduates
- Above position is expected to implement Data Transformation and Data Science integration using python based pipelines deployed using cloud services
- Data Extraction, Transformation, Feature Engineering and algorithm development are the key responsibilities
Responsibilities
- Analyze raw data: assessing quality, cleansing, structuring for downstream processing
- Collaborate with business, design and engineering teams to bring analytical prototypes to production
- Design accurate and scalable prediction algorithms
- Generate actionable insights for business improvements
Basic Qualifications
- Education: B.E./M.Sc./M.E./M. Tech.
- Minimum 1 Year of relevant data science experience
Knowledge & Skills
- Hands on understanding of MS Excel and MS PowerPoint
- Very strong @ SQL and Python
- Interaction with various file formats and databases
- Files Processing – XML, CSV, Excel, Jason, etc. Formats
- Structured and Non-Structured Data processing
Required Competencies
- 1 - 3 years of experience in quantitative analytics or data modeling
- Deep understanding of at least 2 supervised or unsupervised learning algorithms - predictive modeling, machine-learning, clustering and classification techniques
- Fluency in written and spoken English
- Customer Focus
- Good verbal & written English communication
- Ability to work with globally diverse teams
- Readiness to work in flexible work timings
- Abstract & Analytical Thinking
- An interpersonal savvy. A very good team player
- Nimble learning. Willingness to explore and adapt
- Bachelor's degree or equivalent experience in Quantitative or Technical field (Statistics, Mathematics, Finance, Computer Science, Engineering, etc.)