Data Analytics - Lead Data Scientist
Mittlere Stufe (2-5 Jahre), Höhere Stufe (5-10 Jahre)
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The Infosys Analytics unit is focused on driving data-driven decisions at the numerous clients that we work
We aspire to be the leading ‘end to end provider’ in Data Science and Analytics using a combination of skills, technologies and demonstrated value. We are hiring for our analytics team and if you have hands-on experience in delivering analytical projects, we would love to talk to you!
We are seeking an experienced analytics practitioner to join us.
As a Lead Data Scientist, you will:
- Be the key contact at client site while guiding a geo-dispersed team
- Provide guidance on analysis methodologies to the team on a project
- Extract data from source systems such as Oracle, Teradata data warehouses or from primary or secondary research data sources
- Develop data visualizations using tools such as Tableau, Qlikview etc.
- Develop statistical, machine learning or optimization models independently for low complexity projects and with appropriate guidance for medium & high complexity projects using tools such as SAS, R, IBM-SPSS/PASW, LINDO, CPLEX etc.
- Develop modules using Big Data technologies such as HIVE, HDFS, Spark.
- Prepare outputs such as models, model validation reports, data visualization outputs
- Validate results and outputs produced by other Analysts
- Present results of analyses and modeling activities to client stakeholders independently and with support when needed.
- Be responsible for delivering defect free analyses & insights to the customer
In addition, you will contribute to the unit by:
- Participating in proposal creation in response to client requests
- Creating collateral to support sales pursuits
What are we looking for:
- MBA, BE, BS, MS (Math, Finance, Stats, OR, Computer Engg.), or a CFA with relevant experience
- 5 - 8 years of demonstrated experience in Analytics/Big Data.
- Expertise in R/SAS or equivalent analytic tools, visualization tools such as Tableau or Qlikview
- Expertise in Big Data technologies such as HIVE, HDFS, Spark.