- 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
- 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
- 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 Roles and Responsibilities
Desired Candidate Profile
Perks and Benefits
Salary: INR 20,00,000 - 35,00,000 PA.
Functional Area:Analytics & Business Intelligence
Desired Candidate Profile
Doctorate:Ph.D - Any Specialization
Careernet Technologies Pvt Ltd
Contact Company:Careernet Technologies Pvt Ltd