·Conduct analysis to address critical business challenges faced by client teams working in different markets across the banking value chain to recommend the best data and insights powered solutions

· Gathering business requirements to create high level business solution framework covering aspects of banking customer journey, policy & regulatory requirements, data driven business process design & Technology Architecture

·Interface with client teams along with inputs from internal research and data insights teams to develop solutions for identified opportunities across banking LOBs

·Build analytical use cases in AI and Machine Learning across different banking functions including Operations, Treasury and Finance, Risk assessment, Compliance and Regulatory, Fraud, IT and Technology, Product design and Marketing, AI driven Customer Experience

· Ability to work with large data sets and present findings / insights to key stakeholders; Data management using databases like SQL, Oracle, S3 buckets and likes of the same

· You should have worked for 4-6+ years in the area of Knowledge Strategy and Consulting, Analytics and AI Delivery and Business Operations in any of the Tier-1 consulting organizations (McKinsey, BCG etc.) with focus and experience in Banking industry

·Experience in at least some banking function like Operations, Treasury and Finance, Risk assessment, Compliance and Regulatory, Fraud, IT and Technology, Product design and Marketing, AI driven Customer Experience

·Experience in at least some areas of banking domain like Cards/Payments/Retail or Commercial Banking/Digital/Mortgages or Regulatory/Data Privacy/Asset Management/CDD/KYC/AML or Contact Center/Branch Banking along with knowledge of various banking products is required

·Have experience in building analytics models in atleast 1 or more banking function for cross-sell up-sell models, churn models, forecasting models, fraud detection models, AML models, default prediction models, risk pricing models etc.

·Hands on experience in building and deployment of Statistical Models/Machine Learning using following techniques – Statistical Algorithms (at least some of them)
a. Segmentation and Predictive Modeling (K means, Clustering, Multivariate Regression, Logistic Regression)
b. ML algorithms –RF, GBM / XgBoost, SVM
c. NLP algos – TFIDF, Word2vec, LDA
d. Exploratory Analytics (T-tests)
e. Decision Trees

·Experience with some databases preferred like Oracle, TD, Sybase, MS SQL, Win SQL, S3 buckets

·Experience and exposure to developing cloud solutions on AWS/GCP/Azure

·Good experience with Data, Analytics and AI technologies & tools – data native mindset with a deep understanding of Statistics and experience in A/B or multivariate experiment set-up, sharing testing results & recommendations

·Ability of Visual story-telling with BI & Visualization Tools (Tableau/Spotfire/Power BI, Cognos, Business Objects) is preferred

·Advanced Excel including VBA and PowerPoint skills

·Consulting skills Experience preferred

·Excellent written and oral communication skills with ability to clearly communicate ideas and results to non-technical business people

·You are laser focused on delivering outcomes with speed and agility

·You are self-driven and thrive in ambiguity

·MA/MBA/MSc/MPhil.  in Statistics / Economics/ Mathematics / Engg. Degree from Top Colleges in India or Abroad

 Experience:

• 4 to 6 years

Job location:

• Bangalore

Duration:

• 3 months. May get extended.

Joining:

• immediate

We need a proficient PySpark resource with good experience.

Our client, a home appliances manufacturer, wants to understand the past effectiveness of the marketing spend and take decisions regarding their future spend directions. We are looking for providers who could assist us in establishing the impact of key marketing variables.

Position: PySpark Developer

Must Have Technical Skills: PySpark

Good to have Technical Skills: Spark, DWH

·         Hand on experience in Pyspark and Numpy, List, Pandas, Graph plotter.

·         Excellent knowledge of Python framework and Airflow/Luigi/Dagster/Apache Beam.

·         Python skills with all sorts of data libraries, visualization libraries,

·         Good SQL knowledge.

·         Ability to perform multiple task in continually changing environment.

·         Exposure on Hive/HBase/Redis.

·         Good knowledge of Data warehousing.

·         Reading from Parquet and other format.

·         Worked on Hive and HBase.

Nos of Resources required: 3 to 4

Work location: Remote

Qualification: BTech

Experience: 4 yrs – 5 yrs

Mobilization Period in weeks: 1 week

Duration: 3 to 6 months  

SAS Data Quality Consultant:

• Data Quality developer will be responsible for analyzing and understanding data sources and end-user requirements using the SAS DQ.
• Must be aware of Data Quality dimensions and their implementation in SAS DQ tool.
• No of Position-2
• Role & Responsibilities - Dev and Testing Skills
• Experience - 3-6 years of experience
• Location – Delhi NCR