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PHONE:	+9195459	 89457	 www.linkedin.com/in/pawan	-pohani 	EMAIL:	 pawan	.pohani	@gmail.com	 	
     	  	 Pawan	 Pohani	  	
Sr.	 Lead Data Scientist	/Sr. Architect	 	 
 	
 	A  multifaceted  Certified 	Technical  Thought  Data  Analytics  Leader	,  carrying  rich 	
experience  of 	17+  Years	,  with  a  demonstrated	 ability  in  mining  insightful  thought 	
leadership,  strategic  problem  solving,  consulting,	 gauging  the  business  requirements 	
and objec	tives, and be able to transform them into	 use cases as	 projects/business	 pitch	. 	
 	7+	 Years&rsquo;	 hands	-on	 experience	 in	 designing	 data	 driven	 solutions,	 leading	 E2E	 Data	 	
Science/Analytics projects, on prem as well as on cloud, 	and building data solutions	 	
in collaboration,	 with	 different	 stakeholders	 which	 includes,	 but	 not	 limited	 to,	 Product	 	
Team,	 Pre	-sales	 team	 and	 Risk	 Management	 Team.	 	
 	10+	 Years&rsquo;	 experience	 in	 leading	 and	 managing	 multiple	 engineering	 teams	 as	 	
Solution	 Architect	 across	 Waterfall	 &amp; Agile	 Methodology	 and	 various	 technical	 stacks.	 	
 
 	
 	Leadership	 &amp; Strategy	 	
 	Project	 Management	 	
 	Banking	 &amp; Finance	 Domain	 	
 	Cards	 &amp; Payment	 Products	 	
 	Generative AI/LLMs	 	
 	Predictive	 Analysis	 	
 	Collection Analytics	 	
 	Waterfall	 &amp; Agile Methodologies	 	
 	Cognitive Solution	 	
 	Machine	 Learning	 	
 	Artificial	 Neural	 Network	 	
 	Model	 Deployment	 	
 	Azure	/Databricks	 	
 	Deep	 Learning	 	
 	Big	 Data	 Analytics	 	
 	Risk	 &amp; Fraud	 Analytics	 	
 	
 	 	Machine	 Learning	 Techniques	 &ndash; Linear	 Regression,	 Logistic	 Regression, SVM,	 	
Na&iuml;ve	-Bayes, Decision Tree, KNN, Ensemble 	Techniques, PCA, Forecasting, K	 	
Means	 Cluster	 and	 Apriori.	 	
 	NLP	, LLM, Generative AI, 	Deep	 Learning	 &amp; 	Azure 	AI Services	. 	
 	Azure Services 	&ndash; ADF, Databricks, AML, Synapse, Azure AI Services &amp; 	
ADLS.	 	
 	
 	Advance	 Program	 in Data Science	&rsquo; by	 Indian	 Institute	 of Management,	 Calcutta	 	
 	Bachelor of Engineering 	by R.G.P.V. University	 in &lsquo;	Information Technology	&rsquo; 	
branch.	 	
 
 
 
 	
Of	 Note	 	
Experience	 Summary	 	
Qualifications/Core	 Competencies	 	
Educational	 Background

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  	Professional	 Work	 Experience	 	 	
LTI	Mindtree	                                                                                      	Oct/2021	 - Till	 Date	 	
As 	Sr. 	Lead Data Scientist	, provide a technical, consulting and domain	 leadership	 to a team	 	
of Business	 Analysts	, Data Modelling, Data Engineers	 and	 Data	 Scientists	 with	 an	 aim	 of	 	
providing analytical	 solution, to a BFSI client, across various Line of Business. My Roles 	
and	 Responsibilities	 include	 - 	
 Coordinating	 with	 different	 stakeholders	 to identify	 the	 opportunities	 for	 Data	 	
Science/Analytics which	 can	 drive	 relevant	 insights	 for	 Business.	 	
 Brainstorm	 with	 stakeholders	 to derive	 the	 &lsquo;Value	 Realization&rsquo;	/&rsquo;ROI&rsquo;	 	
from	 Data Science use cases	. 	
 Lead the team on requirement gathering, data understanding, defining scope,	 	
building,	 and	 implementing	 solutions	. 	
 Leverage	 different	 Data	 Science	 (Machine	 Learning,	 Deep	 Learning	, NLP	, 	
GenAI &amp; LLM	) &amp; Azure&rsquo;s	 AI	 capabilities to	 build	 the	 solution	/POCs	.  	
 Work with Data Engineering, Data Modelling, Cloud Admin and Power BI team 
to design an end	-to-end solution	, which includes, but not limited to, facilitating 	
data in form of DataMart at cloud and designing PowerBI Dashboards	. 	
Snapshots	 of Projects	 handled	 - 	
 Voice Analytics 	- This use case aims to build an 	Azure Cognitive Solution	 on 	
Unstructured Data to generat	e pre	-defined KPI on English language calls taken place 	
between Relationship Manager (RM) &amp; Customer. With this Business can keep 
close tab on quality of calls from RMs&#039; perspective as well as gauge the pulse of 
customer in terms of products and competitor	s mentioned by Customer.	 	
 Transaction Classification	 &ndash; Leveraging 	LLM (	BERT	) &amp; FastText library	, t	his use 	
case aims 	to categorize	 transactions originating from different sources (NEFT &amp; 	
RTGS) so that Business can gain insights which will subsequently	 help in decision 	
making process.	 	
 Image Processing	 - This use case aims to 	find discrepancies in images of 	
Commercial setup uploaded by Relationship Managers. It leverages the 	LLMs of 	
Azure AI Service	 along with supervised ML techniques.	 	
 Customer Segmentat	ion 	- This use case aims to do Retail Customer Segmentation 	
on different data points, so that Business can have granular details before pitching 
products to customer.	 	
 
   Attra	 Infotech	 	May/2019	 - Oct/2021	 	
As a 	Lead Data Scientist/Architect, have been 	responsible for end	-to	-end Project 	
Management and for Developing a roadmap to tech development in consultation with our 
client teams suggesting solutions to challenges using AI and ML. Roles &amp; Responsibilities 
included	 	
 Lead a team of data scientists &amp; data	 engineers for multiple products/applications. 	 	
 Collaborating with different stakeholders to understand problem statements and 
providing data driven solutions. 	 	
 Lead team on all aspects of Data Mining &amp; Model building. These aspects include, but 
not limite	d to, preparation of Use Cases/POCs (Proof of Concept), Requirement 	
Gathering, Data Acquisition, Data Cleaning, EDA, Data Transformation, Data 
Modelling, Data Visualization, Statistical Reporting, Deployment and Model evaluation 
in production.	 	
Snapshot	 of AI/ML Projects/POCs	 work	ed:	 -

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 Transactions Fraud Prediction Model	: - A 	Classification predictive model 	was	 	
prepared	 to predict	 frauds	 in Banking	 transactions	 (Debit	 Card	 &amp; Credit	 Card).	 	
Chatbot: 	- Presented	 a POC	 of Chatbot,	 using	 IBM	 Watson, at	 Issuing	 &amp; Acquiring	 	
Interface for	 B2B	 Communication. This	 Chatbot	 aimed	 to answer	 queries, give	 status	 	
of Production	 Incidents	 and	 Batches to	 Bank/Financial	 Institute	 representatives.	 	
 Campaign Strategy	: -Historical data shows a healthy conversion rate of Retail	 	
Customers into Credit Card customers. To boost 	the campaign	 strategy of 	the 	
Marketing	 Team,	 a Predictive	 Model	 was	 prepared	 to predict	 potential	 Credit	 Card	 	
customers.	 	
 Product	 Incident	 Analysis	: -Developed	 a model	 to bifurcate	 Production	 Incidents	 	
into	 logical	 groups.	 Group	 Names	 are	 provided	 with	 Logical	 Description	 in synch	 	
with	 the	 respective	 cluster.	 	
 	Data Cleaning, K Means Clustering 	and 	NLP techniques 	were used along with	 	
Python	 3 as programming	 language.	 	
 Card &amp; Payment Data Analysis	: - Client 	provided a data of Indian Banks&rsquo; ATM,	 	
POS,	 Credit	 Cards	 and	 Debit	 Cards,	 with	 an	 objective	 to analyze	 the	 data	 and	 fine	 	
patterns.	 	
 	Data	 Engineering,	 Data	 Cleaning	 and	 EDA	 were	 used as	 framework with	 Python	 3 	
as Programming Language, along with Python 	Libraries 	- Seaborn &amp; Matplotlib 	- 	
used	 for	 Data	 Visualization.	 	
 Ageing	 Categorization	 of	 Production Incidents	: - 	
 	All	 Production	 Incidents	 were	 mapped	 either	 to L1	 Team	 or	 L2	 team.	 System	 didn&rsquo;t	 	
have	 intelligence to	 bifurcate	 ageing of	 Incidents	 with	 respect	 to L1	 &amp; L2	 team.	 	
 	An	 Automated	 process,	 based	 on	 Python,	 was	 developed to	 give	 Ageing	 	
Categorization	 along	 with	 SLA	 and	 Data	 Visualization information	 through	 Tableau.	 	
 Loan EMI Defaulter Prediction 	- This 	use case	 aimed to do Predictive Analysis to	 	
find	 the	 Loan	 EMI	 Defaulters. The	 prediction	 helped	 Risk	 Management	 to strategize	 	
better.	 	
 	Multilayer Perceptron/Artificial Neural Network, Data Cleaning and EDA 	were	 	
used	 as framework	 with	 Python	 3 as programming	 language.	 	
 
Wipro	 	Feb/2015	 &ndash;May/2019	 	
 	
As	 Data Scientist/Architect	, had	 been	 responsible	 for driving	 the	 project	 end	 to end.	 Roles	 &amp; 	
Responsibilities	 include:	 - 	
 E2E Solution Designing of digital and data driven 	projects, which includes close	 	
collaboration	 with	 different	 business and	 tech	 teams.	 	
 Working	 closely	 with	 Business	 &amp; tech	 teams	 to define	 a streamlines	 roadmap	 for	 	
digital	 and	 data	 driven	 projects.	 	
 Served	 an	 onsite	 tenure	 of 6 months	 to ensure	 Data	 Analytics	 project	 gets a	 smooth	 	
start.	 	
Snapshot	 of projects handled:	 - 	
 Risk Strategy Model 	&ndash; Based on historical data, a Classification Model was	 	
developed	 to predict	 which	 all	 Active	 Accounts	 (Debit	 Cards	 as well	 as	 Credit	 Card)	 	
can	 be	 delinquent	 and	 move	 to Collection	 Module. This	 prediction	 was	 be	 used as	 an	 	
input	 by	 the 	Risk	 Management	 Team	 for	 strategizing.	 	
 	Classification	 Algorithm,	 SMOTE,	 Data	 Cleaning	 and	 EDA	 were	 used	 as 	
frameworks	 with	 Python	 3 as programming	 language.	 	
 Cloud Transformation of Legacy Applications	: - With an objective of &lsquo;Application	 	
Modernization&rsquo; 	Capital One has decided to migrate Cards Historical Vision Plus tape

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data from 	Legacy System (Mainframe) to Cloud (AWS) 	in encrypted form and create	 	
a Data	 Lake.	 	
 	Coordinated	 with	 Architecture,	 Client,	 and	 different	 teams	 (spanned	 across	 various	 	
technologies	 - Mainframe,	 JAVA, Unix, Python	 &amp; AWS)	 to finalize	 the	 design.	 	
 	Project&rsquo;s	 scope	 includes	 &ndash; Development	 of tools	 required	 for migration,	 infrastructure	 	
setup and support at Mainframe as well as at AWS, consumption of data at cloud,	 	
automation of	 processes (using DevOps), and continuous rationalization of data to be	 	
migrated.	 	
 	With	 application	 of Data	 Analytics,	 &ldquo;data	 to be	 migrated&rdquo;	 was	 reduced	 by	 30%,	 	
which	 had	 a huge	 impact	 of project	 plan	 (specially	 estimation	 of time	 and	 cost).	 	
 	
HSBC	 GLT	 	Nov/2006	 - Feb/2015	 	
 	
 As	 a Project	 Lead/Onsite	 Coordinator	 for	 HSBC	 Cards	 &amp; Payment	 Portfolio, was	 	
responsible for analysis, estimation, planning, reporting, development, supporting	 	
SIT/UAT	 and	 supporting	 implementation.	 	
 	Worked	 in Vision	 Plus	 Product,	 predominantly	 in CMS	 (Card	 Management	 Service)	 	
&amp; CTA	 (Collection	 Tracking &amp;	 Analysis)	 modules,	 across	 Development	 &amp; 	
Production	 Support	 team.	 	
 	Worked on different functionalities, such as 	Payment Application, Payment	 	
Hierarchy, Payment Processing, Fees 	Processing, Interest Processing and	 	
Collection	 Strategies.	 	
 	Worked as 	&quot;Onsite Coordinator&quot; 	for close to 14 Months across different locations	 	
i.e.,	 USA	 &amp; Brazil	. 	
 	
  	Certification	 &amp;	 Training	 	 	
 	PMP	: Project	 Management	 Professional	 Certification, 2016		
 Databricks	 Accredited Generative AI Fundamentals, 2023	 	
 	Information Technology Infrastructure Library (ITIL) 	Foundation	 