Data Scientist Post by Infosys
Job Description
Responsibilities:
- Enjoy working in complex business environment, refining user requirements, ability to analyze data to answer business queries; adept in quick starting optimization options to solve business problems using latest technologies in data mining, data visualization, statistical modeling, pattern recognition, and optimization across the chosen industry and functional area WITHIN the guidelines, policies and norms of Infosys.
- Define new business metrics as required and build measurement systems as needed.
- Advise clients & internal teams on the right analytical models, analytic platforms and approaches to take in addressing complex, open-ended business problems.
- The job entails sitting as well as working at a computer for extended periods of time. Should be able to communicate by telephone, email or face to face. Travel may be required as per the job requirements.
Technical and Professional Requirements:
- MBA or MS from prestigious University in area of quantitative discipline such as Statistics, Applied Math, Operations Research, Computer Science, Engineering or Physics
- 5-10 years applied experience in exploratory data analysis, devising, deploying and servicing statistical models
- A/B testing, Web analytics, click stream data analysis, and other KPI’s on marketing campaigns
- Fluent in using one or more of analytical tools,
- Python
- Advanced SQL
- Airflow for data pipelines
- Knowledge of visualization tool – Tableau
- Experience with PySpark or Scala will be an advantage
- At least 5 years of domain consulting/BI/analytics experience in one or more of these areas
- Digital marketing analytics, Web Analytics, Social Media Analytics, SEO, paid media analytics, Mobile marketing analytics
Preferred Skills:
-
Analytics->Data Science
-
Analytics->SQL
Work Experience:
- 5-7 Years
Additional Responsibilities:
Knowledge on:
- Python-based Data Science
- A/B testing
- Adv SQL
- Marketing analytics domain knowledge
Educational Requirements:
- Bachelor of Engineering
Service Line:
- Data & Analytics Unit
