Lead - Data Science - BFSI

Responsibilities:

- Person would be required to work individually or as part of a team on data science projects and work closely with business partners across the organization.

- He/she would be developing statistical/machine learning models using various techniques (supervised, unsupervised, semi-supervised) and technologies including but not limited to R, Python, Spark, H2O, Aster etc.

- Work closely with data engineers, BI and UI specialists and deliver top notch analytical solution for the bank.

- Define business problem and translate it into analytical problem

Essential Qualifications:

- BS degree or higher in a quantitative field such as applied math, statistics, engineering, physics, accounting, finance, economics, econometrics, computer sciences, or business/social and behavioral sciences with a quantitative emphasis

- ~8 years of relevant experience

- Excellent command over supervised, unsupervised and semi-supervised techniques including but not limited to Random Forest, GBM, Ridge-Lasso-ElasticNet, XGboost etc. Time-series techniques like Arima (and the family), Arch, Garch etc.

- Experience with Deep-learning, Artificial intelligence techniques like ANN, CNN, DNN, RNN etc. and how to strategize deep-learning layer and activations.

- Experience implementing machine learning algorithms such as support vector machines, decision trees, logistic regression, clustering, neural networks, graphical models etc.

- Excellent understanding of model metrics including AUC, ROC, CAP-curve, F-statistics etc. with clear understanding of how model performance is tuned

- Strong programing skills.

- Expertise in analytic tools : R, Python, Scala, Java

- Big Data skills - Aster, Hadoop, SPARK, H20 and various big data distributions like Hortonworks and MapR

- NLP, Text mining, Image/Voice processing, digital analytics, deep learning, machine learning

- Demonstrate excellent organization skills throughout the development of analytical solutions (data analysis documentation, hypothesis documentation, code management, etc.).

- Data Engineering

- Sql, Teradata, Hadoop, Spark

- Exploratory Data analysis

- Provide exploratory data analysis using Python/R/SAS / SQL

- Experience with Databases like oracle, Teradata, Sql server

- Advance Excel skills

- Data integration and clean up data for the usage

- Experience with structured data and semi-structured text or Excel files

- Business Intelligence

- Tableau, Power BI, Shiny, Dash, HTML5

- Business Analytics

- Data mining and Insights

- Trend Analysis, forecasting and pattern recognition

- Find opportunities in the data and able to communicate to the partners

- Consult with partners to define issues/information needs

- Present findings to multiple levels of management

- Ensure that analyses are delivered on time, while surpassing partner expectations

- Ensure partner transparency throughout the life of the project

- Proactively seek opportunities to increase the value of analysis

- Strong oral and written communication and consultative ski

Desired Qualification:

- Strong collaboration skills

- Output deployment using appropriate technologies (HTML5, Shiny, Django)

- Working expertise in Tensorflow, Keras or Pytorch would be added advantage

- Ability to translate analytical data into useful business information

- Critical thinking and strong problem solving skills

- Ability to learn the business aspects quickly

- Knowledge of banking industry and products in at least one of the LOB such as credit cards, mortgage, deposits, loans or wealth management etc.

- Knowledge of functional area such as risk, marketing, operations or supply chain in banking industry.

- Ability to multi-task and prioritize between projects

- Ability to work independently and as part of a team