Lead Data Scientist-Digital Banking Kotak 811-Regional Sales

Bengaluru, Karnataka, India

Kotak Mahindra Bank

Kotak Mahindra Bank offers high interest rate savings account, low interest rate personal loan and credit cards with attractive offers. Experience the new age Personal Banking and Net Banking with Kotak Bank.

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Lead Data Scientist – Kotak811
Kotak811 is a Neobank incubated by Kotak Mahindra Bank, with a view of providing
completely digitized banking services in the convenience of the customer’s mobile phone. 811
is an early mover in the Indian fintech space that started off as a downloadable savings bank
account in 2017, post demonetization, when India took one step closer to a digital economy.
The Senior Data Scientist in Bangalore (or Mumbai) will be part of the 811 Data Strategy Group
that comprises Data Engineers, Data Scientists and Data Analytics professionals. He/she will be
associated with one of the key functional areas such as Product Strategy, Cross Sell, Asset Risk,
Fraud Risk, Customer Experience etc. and help build robust and scalable solutions that are
deployed for real time or near real time consumption and integrated into our proprietary
Customer Data Platform (CDP). This is an exciting opportunity to work on data driven analytical
solutions and have a profound influence on the growth trajectory of a super fast evolving digital
product.
Key Requirements of The Role
● Advanced degree in an analytical field (e.g., Data Science, Computer Science,
Engineering, Applied Mathematics, Statistics, Data Analysis) or substantial hands
on work experience in the space
● 6 - 12 Years of relevant experience in the space
● Expertise in mining AI/ML opportunities from open ended business problems
and drive solution design/development while closely collaborating with
engineering, product and business teams
● Strong understanding of advanced data mining techniques, curating, processing
and transforming data to produce sound datasets. Strong experience in NLP, time
series forecasting and recommendation engines preferred
● Create great data stories with expertise in robust EDA and statistical inference.
Should have at least a foundational understanding in Experimentation design
● Strong understanding of the Machine Learning lifecycle - feature engineering,
training, validation, scaling, deployment, scoring, monitoring, and feedback loop.
Exposure to Deep Learning applications and tools like TensorFlow, Theano, Torch,
Caffe preferred
● Experience with analytical programming languages, tools and libraries (Python
a must) as well as Shell scripting. Should be proficient in developing production
ready code as per best practices. Experience in using Scala/Java/Go based
libraries a big plus
● Very proficient is SQL and other relational databases along with PySpark or
Spark SQL. Proficient is using NoSQL databases. Experience in using GraphDBs
like Neo4j a plus. Candidate should be able to handle unstructured data with
ease.
● Candidate should have experience in working with MLEs and be proficient
(with experience) in using MLOps tools. Should be able to consume the
capabilities of said tools with deep understanding of deployment lifecycle.
Experience in CI/CD deployment is a big plus. Knowledge of key concepts in
distributed systems like replication, serialization, concurrency control etc. a big
plus
● Good understanding of programming best practices and building code artifacts
for reuse. Should be comfortable with version controlling and collaborate
comfortably in tools like git
● Ability to create frameworks that can perform model RCAs using analytical and
interpretability tools. Should be able to peer review model
documentations/code bases and find opportunities
● Experience in end-to-end delivery of AI driven Solutions (Deep learning ,
traditional data science projects)
● Strong communication, partnership and teamwork skills
● Should be able to guide and mentor teams while leading them by example.
Should be an integral part of creating a team culture focused on driving
collaboration, technical expertise and partnerships with other teams
● Ability to work in an extremely fast paced environment, meet deadlines, and
perform at high standards with limited supervision
● A self-starter who is looking to build grounds up and contribute to the making
of a potential big name in the space
● Experience in Banking and financial services is a plus. However, sound logical
reasoning and first principles problem solving are even more critical
A typical day in the life of the job role:
1. As a key partner at the table, attend key meetings with the business team to
bring in the data perspective to the discussions
2. Perform comprehensive data explorations around to generate inquisitive
insights and scope out the problem
3. Develop simplistic to advanced solutions to address the problem at hand. We
believe in making swift (albeit sometimes marginal) impact to business KPIs and
hence adopt an MVP approach to solution development
4. Build re-usable code analytical frameworks to address commonly occurring
business questions
5. Perform 360-degree customer profiling and opportunity analyses to guide new
product strategy. This is a nascent business and hence opportunities to guide
business strategy are plenty
6. Guide team members on data science and analytics best practices to help
them overcome bottlenecks and challenges
7. The role will be an approximate 60% IC – 40% leading and the ratios can vary
basis need and fit
8. Develop Customer-360 Features that will be integrated into the Customer
Data Platform (CDP) to enhance the single view of our customer
Website:
https://www.kotak811.com/

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Banking Caffe CI/CD Computer Science CX Data analysis Data Analytics Data Mining Data strategy Deep Learning Distributed Systems EDA Engineering Feature engineering FinTech Fraud risk Git Java KPIs Machine Learning Mathematics MLOps MVP Neo4j NLP NoSQL PySpark Python RDBMS Scala Shell scripting Spark SQL Statistics TensorFlow Theano Unstructured data

Perks/benefits: Career development

Region: Asia/Pacific
Country: India
Job stats:  3  0  0

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