Senior Advanced Analytics Head

Job Description

* Duties and Responsibilities - Managing the End to End Capability & Creation of Data Sciences Capability based Initiatives across the organization. This unit works primarily on creating viable and business driven capability which includes AI, ML & Data Unit. The key areas of capability are the following. Manage @ scale data science projects & capability across the organization @scale delivery (team & partner) Creation of @ scale Data Science models with business consumerization Leading Cross functional engagements including business, support functions like IT, etc. Proactive Management/team management/building of skilled teams in AI, ML & Data related programs Data Science Subject Matter Experience (algorithmic level) Basic Qualifications: 1. Minimum 20+ years of industrial experience in managing hands on AI based capability across large data and business driven use cases. 2. Strong educational background in mathematical, statistical and data science orientations (PhD (Computer Science, artificial intelligence, Data Mining, Mathematics, Statistics. ) PhD (computer science | data sciences with industrial experience) is mandatory 3. Hands on experience in data science algorithms and working in medium to complex business problems is mandatory. 4. Strong understanding of data science languages such as (R,Py) along with strong solution experience with Data Science technology implementation architecture is mandatory. 5. Experience in advanced models (theory and implementation). Working with large open and cloud scalable platforms. 6. Demonstrated proactive leadership in the management of fields of Data Science Capability is mandatory 7. Strong techno-functional management working with business teams (on business use cases/ programs) 8. Management of Data Science Teams which includes core data science engineers & partners @ algorithmic depth 9. Strong architectural inclination and has participated/contributed @ core design levels with ability to manage /work on complex large projects is must 10. Strong IT & Business interactions capability 11. Strong hands-on nature (ability to understand-code (base level) / ability to tech mentor - must) for team members 12. Strong team player with exceptional program management (execution). Self-driven & high ownership levels are key 13. Constantly ahead of curve in latest Data Science related technologies and capabilities that are relevant to BFL/ Business 14. Ability to think understand complex business requirements and render them as prototype systems with quick turnaround time. 15. Strong verbal and written communications skills are a must, as well as the ability to work effectively across internal and external partners/virtual teams. 16. Strong team working and working with grounded collaborations (inter and intra teams) 17. Well connected with eco-system for technology and data science. Diverse domain spread in Data Sciences is a must 18. Capability must be referenceable , * PREFERRED QUALIFICATIONS 1. Strong Experience with Strong Data Science, Statistics, Machine Learning & Modeling @ implementation level 2. Working knowledge of modern software development practices and technologies such as agile methodologies and DevOps 3. Technical degrees in computer science and very comfortable with algorithmic models and implementation 4. Prior Large Enterprise Participation | Consumerisation | Implementation experience in the Big Data Ecosystem, (such as Hadoop, Spark, R|Py, Hive), Production scale Database (such as Oracle, MS SQL Server, MySQL, PostgreSQL), NoSQL (such as HBase, MongoDB, Cassandra, Cosmos, Arango, Orient) and Data Warehousing (such as Microsoft Azure DW, Redshift, Teradata, Vertica) and data migration, ETL and integration.

Keyskills :
mssql sqlserver ssqlserver bigdata edata