Mohammed Jawed Khan is an Indian national who currently works as a Data Scientist in Saudi Arabia. He has over 15 years of experience in business analytics, data science, and machine learning. He holds a Master's degree in Business Analytics and has received several certifications in predictive modeling, Six Sigma, and SAS programming. Khan has worked on a variety of analytics projects for companies in sectors like automotive financing, insurance, and energy. His responsibilities have included developing predictive models, forecasts, marketing campaigns, and tools to optimize business processes.

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Resume
Personal Details
Name Mohammed Jawed Khan
Email mohjkhan@indiana.edu
Mobile +966-568121688
Nationality Indian
Marital Status Married
Date of Birth 03 Oct 1975
Role: Data Scientist
Qualifications:-
Graduation: Master of Science, Business Analytics (2015)
Kelley School of Business, Indiana University, USA.
Under Graduation: Bachelor of Technology, I.I.T New Delhi (2001)
International Languages:-
i. English (TOEFL-293/300 and 5.5/6 essay)
ii. German (DSH Universität Stuttgart-Bestanden).
Certification:-
i. Graduate Certificate in Business Analytics (2014) IIM-Lucknow.
ii. Certified Predictive Modeller SAS Enterprise Miner 7 from SAS
Institute
iii. Six- Sigma Master Black Belt Certification from Indian Statistical
Institute.
Business Analytics Tools:-
Oracle Crystal Ball, Advance Excel (@RISK and the Decision Tools
Suite, Power Pivot), POM-QM.
Python, Matlab, SAS Enterprise Miner, JMP, SPSS.
BI-Tools: QlikView, Tableau, Excel Visualization
Programming:-
Base SAS, Java/ J2EE, Python, R, Visual Basic, MS/Unix Script, PL/SQL

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Professional Experiences:-
1. Operation Management (ALJF) (Jan’12- current)
Role: Data Analyst; Location: KSA
About Company: ALJUF is the market leader in providing Auto finance
to its customers whether fleet or consumer finance. It facilitates sales
of new and used Toyota & Lexus vehicles through its leasing and
instalment portfolios. It has a network over 230 branches spread over
the country and its current receivables is around 17 billion SAR.
My role in the company has been initially to initiate Risk Modelling
solutions for various departments using COSO framework, develop
resource and process to mature ALJ in Analytics based company, and
finally lead the road map to the ambitious and high invested endeavour
to integrate Enterprise Analytics.
i. Maximize collectors’ performance.
Challenge: ALJUF is reducing number of collectors which will reduce
available collection efforts. This may directly impact the overdue of the
company. The task was to optimize available collection efforts (call,
SMS, legal action) with the limited number of collectors without
adversely affecting the overdue of the company or alienating profitable
customers. Collection effort was customized according to identified risk
groups.
Based on customer characteristics, a statistical model based on survival
analytics is developed, to identify by when a particular guest should
have paid their overdue. If payment was not received by this time, the
system triggered Agents to apply or intensify collection efforts.
Different collections efforts have different cost, and designing
appropriate effort will optimize collection operation cost.
Specific risk profile guest receive customized messages at appropriate
time, providing them time to act before the next level collection effort is
employed. Guests are called only when payment is not received until
the model suggested time. This will reduce the number of Guests to be
called by the collectors thus reducing collectors call effort.
Guests whose payment time is suggested by the model beyond the
current month should be proactively contacted from the beginning of the
month thus avoiding their delinquency. Collectors receive their specific
list to call/SMS which facilitates them to optimize their work.
Customer feedback using text mining was used to update customer
records and sentiments/follow ups.
ii. Target Forecast System: - ALJL requires forecasts of sales and
collection projects monthly targets at each hierarchy of branch staff,
supervisor, branch manager, AGM and Director based on historical
patterns using statistical methods. This is used to evaluate
performance of branch staff and evaluate commission of staff of

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profit centres. The historical time series sales and collection monthly
data of length 10 years was collected from FS-System. The seasonal
effect and periodicity was identified and filtered using adjusted
moving average method. The remaining effects were those of cyclic
components which was modelled using Fourier analysis and distinct
frequencies were identified. Finally diagnostic checks were
performed on residual (irregular) as free from autocorrelation or
partial autocorrelations till 30 lags through Box-pierce statistics.
iii. Marketing Campaign: Led the development of Analytic List for
targeted solicitation of potential repeat customer. The ensemble
model prioritise potential customer based on recommended
probability from decision tree, neural network, gradient boosting,
logistic regression. The recommending also suggested the preferred
product and the time of solicitation based on Survival Analytics. The
model suggested the communication channel as well as the time to
broadcast the promotion for specific customer. Using text analytics of
campaign feedback, campaign analysis success was measured.
iv. Application Score Card: - I design and development of Customer
Score Card (customer credit worthiness assessment) based on
training a predictive model using Statistical methods with existing
customer based on their payment behaviour and customer
demographic profile. This model predicts score evaluated for each
application. The trained model through regression model, decision
tree and neural net provided prediction on test data with reasonable
accuracy. Thus a predictive engine for new customers provided a
score which became a basis of considering them for new lease
application.
v. Bad Debt provisioning criteria: - The Company has every month
outstanding receivables on which bad debt provision is to be
ascertained in an optimal way using “Flow method Approach”. Based
on historical collection pattern, a series of segments were created
based on activity and months overdue applied at contract level thus
achieving lower bad debt provisioning to Basel II capital framework.
2. IBM Research (Oct’06- Jan’12)
Role: Business Analyst Location: Stuttgart, Kassel (Germany)
i. Daimler AG: IBM Daimler Chrysler (IVK) was developed to solve
Constructive Problems during Configuration as Model Construction
for customization of design and configuration of Lastwagen.
Constraint solver Engine was IBM product and we utilized to
compute minimum conflict goals while solving interactive system
constraints during dynamic formulation of Daimler vehicles. The
challenge was to translate vehicle configuration constrains into
proportional logic to model dependencies and finite domain
constraints to represent conflicts. We also customised the Constraint
Solver’s minimal conflict solver engine to pick solution from sub
optimal space to provide for consideration on time and memory
optimisation, even though constraint suspension was accommodated

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by tolerable threshold. This was quite an innovation and stimulating
team from cross cultural team from IBM Germany, India and Israel
and we could implement state of art solution.
ii. Volkswagen: Volkswagen AG Ersatzteile 2000 is an IT-logistic parts
ordering system forms the backbone for the supply of spare parts
for the VW and Audi dealerships Kassel warehouse. ET2000 had
capacity issues and poor responsiveness due to limitation of their
base EOQ model in handling some of the slow moving parts which
always had to be backordered at a cost, hence enhancement was
required. Using Demand forecasts of each slow moving Auto parts
based on historical data on demand and model variability in lead
time and applying Quantity discount models, a stochastic model to
control inventory was developed to generate reorder quantity and
reorder schedule to optimize inventory at each Tier of integrated
distribution system. To avoid stock outages, safety stock amount
was derived from the stochastic model.
3. Morgan Stanley (Apr’04 2004 till Oct’06)
Role: Associate; Location: Geneva (Switzerland).
Projects: MSCI BARRA Index creation
MSCI provides global equity indices, which, over the last 30+ years,
have become the most widely used international equity benchmarks by
institutional investors. Barra is the market leader in delivering
innovative, financial risk management solutions worldwide.
I was appointed as Associate and my work comprised of Modelling &
Analysis of MSCI indices creating market segmentation of portfolio
grouping for advising investors. Capital Investment for MSCI Barra
Index at Geneva which resulted in optimal portfolio creation based on
Risk and Return Period Profiles.
4. Project Associate, IKE, Germany (Feb’02 – Mar’06).
Role: Associate; Location: Stuttgart, Germany
Projects: ECA
This project was developed by Institüt für Kernenergie Energiesystem
(IKE) to create simulation model of Energy usage in school building. A
generic data model was used to define building components and
associating energy loss parameters. The model was then subjected to
different schedule profiles and subjected to varying Heating, Ventilation
and Air Conditioning (HVAC) conditions. This resulting energy usage
was fed to the Energy Concept Advisor (ECA) tool which was developed
to give retrofitting advice for building energy optimization.
5. AIIMS, New Delhi (Jan’01– Jan’02)
Role: Associate; Location: New Delhi, India
Projects: Department of Science and Technology, Government of India
The project was to create a disability correction tool through presenting
acoustically modified learning programs for dyslexic children.

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Publication:
Policy paper on Energy Concept Advisor.
http://www.annex36.de/eca/de/06util/pdf/A36SubtaskC_Appendix_ECA.pdf
Training/Internship
May’00 - Aug’00 Research Associate, Lehrstuhl für Mustererkennung
und Bildverarbeitung, Institüt für Informatics; Freiburg Universität.
Project I: Development of correction parameter table for a scanner
which scanned a colour palette of combination of 64 colours and showed
discoloration. With statistical methods, the colour table could map to its
original colour combination from RGB.
Project II: Robot vision program which identified the corners of cubes
using shortest path technique where curvature of line plot showed rapid
change is curvature.
Recommendation:
1. Prof Dr Fritz Schmidt (IKE, Stuttgart University) - Pensioner
2. Prof Dr Ash Soni (KSB, Indiana University)
3. Prof Dr Venkataramanan (KSB, Indiana University)
4. Prof Dr Frank Acito (KSB, Indiana University)
5. Prof Dr Yogesh Agarwal (Indian Institute of Management, Lucknow)
6. Prof Dr Gaurav Garg (Indian Institute of Management, Lucknow)
7. Prof Dr Amit Agrahari (Indian Institute of Management, Lucknow)
8. Prof Dr R K Srivastava (Indian Institute of Management, Lucknow)
9. Prof Dr Veena Kalra (All India Institute of Medical Science, Delhi)
10.Prof Dr Prem Kalra (Indian Institute of Technology, Delhi)