Manager - Machine Learning Modeling - Financial Domain

For those who love to build large ML capability and see the joy of it being used in a very agile and dynamic environment. This role provides the ability to work @ scale and challenge yourself (agile working approach).

Core ML Model development for business and horizontal capabilities

- Develop & Deliver ML projects across the organization @scale delivery & capability levels for real-world business-related use cases

- Development (both Individual Contributor & working with team & partners)

- Minimum 7 years of core ML work experience (hands-on)

- Must have worked in Financial Domain (financial domain must - NBFC preferred)

- Strong Cross functional engagements including support functions like IT, etc.

- Strong Data Science Subject Matter Experience (Understand ML Algorithms & how to implement at scale | plus constantly self-learning advanced capability)

- Must be currently hands-on - Strong Data Science Coding Level (Near Production / High Quality Code)

- Languages :R|Python|Spark|Java|Scala (Strong Coding skills required)

- Strong IT & Business interactions capability

- Constantly ahead of curve in latest Data Science related technologies and capabilities that are relevant to BFL/ Business

- Ability to think understand complex business requirements and render them as prototype systems with quick turnaround time.

- Strong verbal and written communications skills are a must

- Nice to have capability to work effectively across internal and external partners/virtual teams

- Strong team working and working with grounded collaborations (inter and intra teams)

- Strong sense of humility is a must

- Strong educational background in mathematical, statistical and data science orientations (masters level preferred)

- Mandatory Technical Skills (Hands - on required)

Big Data Ecosystem, (such as Hadoop, Hive, Spark),

Languages - Spark, R, Py, Java (Mandatory)

Production scale Database (such as Oracle, MS SQL Server, MySQL, PostgreSQL),

NoSQL (such as HBase, MongoDB, Cassandra, Cosmos, Arango, Orient)

Data Warehousing (such as Microsoft Azure DW, Redshift, Teradata, Vertica)

Cloud based infrastructure | Notebook | Docker

Operating system Linux knowledge (Mandatory)