Navin Sinha, Ms, Mba Email and Phone Number
Owner and CEO at Double Check Consulting (BPO): #AI 4 #Healthy #Food and #Humans at
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Double Check Consulting
Navin Sinha, Ms, Mba's Location
Fremont, California, United States, United States
Navin Sinha, Ms, Mba's Contact Details
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Navin Sinha, Ms, Mba phone numbers
About Navin Sinha, Ms, Mba
My passion is Health Tech, Ed Tech and Agritech. Double Check Consulting has executed projects smartly since September 2012 made very notable presentations in Silicon valley, CA on Prescription Drug Fraud (Milpitas, CA), Readmission Algorithm Predictive Analytics Research (Pleasanton, CA), Car Injury Fraud presentation (Sunnyvale, CA), Completion of four year Calciferol Drug Adherence Clinical Research in 2017 in collaboration with Arogya (Disease Free) Orthopedic Surgery Center from Patna, Bihar, East India (this data will never be available in USA due to legal and regulations), Hospital Patient Charity Predictive Analytics and, ACO/ Kidney Treatment Analytics from Hospitals of California (Hospital Manager Association, Modesto, CA). All these presentations address At Least $2.0 Million Dollar savings per Quarter with technology encompassing AI and Machine Learning Algorithms, Double Check Consulting featured in Hacker Dojo Lightening Talk Platform (“Career Transition into Analytics”, 5th June 2015) in MT. View, CA. We believe in finding hidden talents and matching job opportunities with those talents in each person for win-win to all parties involved. Hence, Double Check Consulting partnered with Fluent Analytics and presented,” Career Advancement in Analytics” on June 4, 2015 and Analytics and BI” webinar on July 2, 2015. With a watchful eye on research, we develop partnership with Academia and Industry in USA and India; particularly in AI and Machine Learning Algorithms. We believe in innovations and scalable partnerships that respects client's resources. Double Check consulting tool is driven by Communication and Transparency of Analytical methods. Our tool rewards talents for curiosity and critical thinking; emphasis is finding Datastory and communications that impacts bottom line positively.In Agritech, my focus is develop products that makes world a better place to live. The solutions, for example, are for hunger and food waste. I've developed sweetest tomato variety in USA. "waitNOmore" is another variety I developed that has 9 months and continuing shelf life. Certainly such an outlier shelf life means it has anti-fungal and antibiotic properties. It could help us find anti-aging and longevity genes in humans. I've also silenced heat shock Proteins (HSP) in tomato plants of certain phenotype; similar research with HSP in Lung, Brain and Ovarian cancer can result into longevity of patient's lives.
Navin Sinha, Ms, Mba's Current Company Details
Double Check Consulting
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Owner and CEO at Double Check Consulting (BPO): #AI 4 #Healthy #Food and #Humans
Navin Sinha, Ms, Mba Work Experience Details
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Chief Executive OfficerDouble Check Consulting Sep 2011 - PresentNoida , Up , InWith world class education and 30+ years of experience in applied mathematics, I’m a focused executive with a strong background in Retail, Healthcare, Energy and Utilities, Genomics, Agriculture, Property and casualty and eCommerce. My experiences includes outstanding presenter/lecturer, skilled negotiator with superior leadership skills, excelled in multiple industries, disciplines and geographies with strong track record of building great teams and operational wins while delivering exceptional results. My experiences include client facing interactions and customer experience prowess, dynamic public speaking and an innate ability to recognize and rapidly exploit revenue opportunities.My objectives are to bring quality, innovation, and production of services to my clients at cost effective means. They must save or make money; otherwise we've no purpose! Strengths are a revenue generating driver with bottom line and operational efficiency focus, passionate and insightful team oriented leader with integrity, capable of quickly establishing and sustaining long-term relationships to create mutually beneficial synergies. Successful history in operations, possessing the vision and strategic acumen to anticipate market challenges and opportunities, and the dexterity to execute creative products and solutions.
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Retail / Ecommerce Sales Analytics Data Scientist ConsultantAbc Ecommerce Company Aug 2012 - Oct 2012• SEMI-SUPERVISED and UNSUPERVISED Algorithms Creation for Efficient Utilization of Big Data Tools; measure events such as signal or sale and outlier event such as noise or no sale. • Data Science Questions for Hypotheses and correct Interpretation for bottom line profitability- what is the Noise (no sale)/ signal (sale) ratio in a given month/ year? How much it depends upon sellers, ads and products (item price) sold? What visual analytics patterns can be extracted from Pricing strategy and buyer patterns? Look at seller and what time and price they sell. If they sell at holiday time only when they can get more money, can we call them loyal? Statistical Methods Exploration to answer pricing strategy questions: - RBF Kernel Smoothing and Time Series Segmentation• Contributed to the product vision/ Visualization tool design and development (spec and UI Design growing pains); Text Mining the negative and positive feedback to calculate Net Promoter Score. This helped to understand if Anti-Fraud products were helping in reducing negative customer experiences (stolen goods sold that were in a bad shape/ not working well etc) and quality of sales driven by Advertisements (product sold was quickly returned by customer after the feedback that characterized "purchase based on misleading ads").• Presentation and Interaction with senior management.
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Data Scientist Manager Consultant (Property And Casualty Fraud)Saama Technologies Jun 2012 - Aug 2012Campbell, Ca, Us*BACK PROPAGATION NEURAL NETWORK: Healthcare Fraud Scoring based on car make, color etc for Fortune 100 company from Property and Casualty/ insurance and Technology industry.*Analyzed several Propriety and Syndicated databases on SPSS 12.0; Fraud Analytics Tool Development.* Innovation: Experiments with Statistical Methods and Development of new predictive analytics methods to manage difficult data quality. Escalated Project was delivered with Technical and Business vision (Hypotheses, Test and Validate).* Leadership: Managed TWO POCs Analytics plus mentored offshore senior analysts in car insurance Fraud and Semiconductor industry towards successful project completion. **POC Demystified:- how to go from 0$ to $$$$$ in couple months. -
Lead Project/ Program Manager (Medical Informatics) ConsultantBlue Shield Of California Mar 2012 - May 2012Oakland, California, Us*Accountable Care Organization (ACO) Analytics- Sampling distribution of sampled Mean Length of Stay (1-30, 31-60, and 61-90 days), analytical assumptions and bias in correlation/ association estimates. * Analytics Infrastructure Solutions Diagramming (Service Oriented Architecture: SOA)- SAS code review, requirements gathering, infrastructure, client report comparison with Business Object and coding gap analysis, PowerPoint and Executive presentation for 30 different clients. * Business Process Mapping and documentation- requirements gathering, Six Sigma, documentation, PowerPoint, and Executive Presentation. * Healthcare Utilization (medicine and surgery) driven by Fraud. -
Retail Big Data Scientist Independent ConsultantTransera Feb 2012 - Mar 2012Gaithersburg, Md, Us* Selected by CEO for a difficult task of developing Sales/ Marketing Analytics Value Proposition (VPE) from cutting edge Big Data IT Infrastructure that included Splunk, Pentaho, Jaspersoft, MapReduce, TOAD Hive.* Suggested and after approval from CEO, showed in data Why and How Big Data Healthcare Fraud, Genomics and Gene Chip Analytics Methods Achieve Marketing ROI for Communications Industry where Revenues are made by Selling Products over the Telephone. -
Manager-Healthcare Fraud And Utilization AnalyticsMedsolutions Oct 2011 - Jan 2012Bluffton, Sc, Us• Utilization VS FWA Analytics- how much of Utilization is driven by Fraud, Waste and Abuse?. • Cardiology Fraud- Interacted with marketing department towards development Cardiology Product by providing 360* view on Cardiology specialty fraud and related segments (sleep apnea) in commercial population. Statistical Analysis detected a total of 4 million $ aberrant billing in commercial population. • Utilization Analytics- Higher order nonlinear statistical models on frequency data indicated continuation of Wasteful and Abusive provider practices even after tort reform in TN. It also showed unnecessary patient care in specialties such as Neurology (healthcare policy analytics). • Experiments with Six Sigma Methodology for Data Quality Methods innovation and correct Physician Profiling/Radiology Fraud.• Advised Senior Management on Advance Analytics Techniques such as LASSO, Elastic Net, Linear Stagewise Regression, Least Angle regression in healthcare fraud. • Made presentation to Senior Management on Neural Network and Decision Tree -
Healthcare Business Development Independent ConsultantUst Global Sep 2011 - Jan 2012Aliso Viejo, Ca, Us* BCG and Swot Analysis of Client's healthcare customers' products and services. * Delivered SWOT Analysis of Customer's IT and Analytics process and services to CEO. * Flew with Senior Executives for Sales Pitch to >1.0 Billion $ Project Spending authority; forming 80:20 contract signing. It resulted in 20 FTE from 0 immediately, and 80 FTE after 6 months of good quality project results. *Taught, Trained and managed client's resources towards a successful Healthcare Fraud seed project worth 5-10 million $ from CMS/ federal agency; resulting into IT-to- Healthcare Fraud Analytics conversion for the company. -
Lead Healthcare Fraud ScientistVerisk Health Aug 2010 - Aug 2011Waltham, Ma, Us-Presented 360* analysis of Healthcare industry and Vision on healthcare outcome to VP.-Decision Tree (CHAID) on ETG/ health outcome data to validate fraud variables, business rules and patterns found by Genomics methods. -As the Lead Scientist conceptualized the Healthcare Insurance Fraud Product Market based upon federal healthcare policies and laws. Successfully wrote Healthcare Fraud Analytics Product Vision and presented to the VP. -Applied Linea Regression, Cluster analysis, Neural Nets, Memory Based Reasoning and discriminant analysis on ETG confinement table data and created variables for claim Line scoring predictive modeling. -Demonstrated thorough understanding of healthcare claims data, Episode Treatment Group and Evidence Based Medicine (EBM Connect, Ingenix) data towards attaining high predictive lift.-Created Standardized Analytical Objects such as Clinical Variables on SAS Enterprise miner. -Demonstrated sense of urgency for clients by conceptualizing and creating 500 variables for Healthcare FWA within one year. Convinced client on appropriateness of several variables used in Predictive modeling over phone; creating new business revenues. -Influenced client on creation of several insightful variable for predictive modeling-saving 10 Millions in a year from FWA.. -As SME, wrote Several Strategic Documents that were executed by VP and the client CEO.-Innovation: Exploration Analytics with Logistic Regression, Neural Network, Decision Tree towards false positive reduction in Medicare fraud. -Gained deep respect and traction from client on Provider Fraud Predictive modeling (scoring) project due to Excellent production performance. -
Independent Cancer Data Mining ConsultantCity University Of Ny (Cuny) Jan 2009 - Jun 2010New York, Ny, UsConducted complex mathematical simulations such as Dynamical Simulations and Reverse Engineering Algorithm simulations in support of cutting-edge cancer research led by world-class tumor scientists. Acquired expert knowledge on breakthrough research and served as a valuable mentor to PHDs participating in ongoing tumor studies. Generated actionable hypotheses and prepared Power point for the Principal Investigator towards a very successful Predictive Modeling presentation at Harvard Medical School on 18th June, 2009. An "Invited Speaker" at University of Minnesota on “Predictive Modeling, Mathematical Simulations and Data Mining: Making Sense out of Really Difficult Cancer Data”, by American Statistical Association (Minneapolis) on October 23, 2009; a Leadership recognition based upon the creative use of Retail Industry Reverse Engineering Algorithms in Healthcare towards a successful drug discovery ($).Besides Bio-pharma drug companies, it has "Actionable Solutions ($)" towards appropriate Healthcare Utilization Outcome for medical insurance companies and, Retail Industry (YouTube details in the website section on profile). This project found how best to achieve actionable solutions based upon the findings of this research (Brain Tumor Clinical Trial Loss Mitigation- $). It was featured by prestigious Biotech drug discovery think tank, World BIO-IT EXPO 2010 as Top 100 Data Mining Innovations of 2009 from world wide Bio-mathematical modeling, on April 21-22 Healthcare Conference in Boston, USA. -
Healthcare Fraud Business Development ConsultantSatvik Analytics Oct 2009 - Apr 2010Piscataway, New Jersey, Us*Invited by CEO and traveled to India in November 2009 and March 2010 to present the Healthcare Fraud Vision. * Selected and Interviewed candidates for Sales personal in USA and made the recommendation to the CEO. * Mocked up healthcare insurance fraud data and mentored the Satvik analysts on how concepts of six sigma finds out aberrant billing providers from database. . * Final Feasibility Report was delivered to CEO in March 2010. -
Statistical Project ManagerWipro Consulting Mar 2008 - Dec 2008Bangalore, Karnataka, InExpertly managed resources and delivered detailed predictive modeling as well as data mining reports for information technology (IT) infrastructure consulting company with $100 million in revenue. Managed and mentored junior analysts in the retail client coverage division and specialized in customer attrition modeling, brand valuation metrics, and cross-shopping investigations. Contributed expertise to successfully execute the Intuitive Customer Experience (ICE) banking project by evaluating 300 unique variables and 25 strategic business initiatives, improving quarterly loss mitigation from sub-prime customers by 20%.Managed resources and discovered significant savings embedded in customer charge-off practices for Capital One. Identified a greater likelihood of default among Capital One customers with both an auto loan and credit card, calculating a 50% greater risk of a charge off compared to customers with only a Capital One credit card. Utilized the Odds Ratio, Relative Risk, and Relative Difference methods to fully quantify findings for senior management. Efforts resulted in $3 million in savings reduced credit exposure to sub-prime borrowers and $1 million in revenue from targeted marketing programs. Completed non-compete agreements. -
Senior Data Analysis ConsultantXcel Energy Jul 2007 - Jan 2008Minneapolis, Minnesota, UsAggressively retained by leading green energy producer ($5 billion in sales) to build, develop, and maintain FEED FORWARD NEURAL NETWORK Models to differentiate between seasonal trends and customer tampering activity to more accurately measure energy use and efficiency. Efforts corrected 200 mal-performing energy meters from across the northern mid-west and southwest United Sates (Minnesota to Texas) in 2006. Authored an extensive performance analytics research document that showed how different statistical methods eliminated false positive and negatives, and established a company-wide actionable solution resulting in $1 million expense saves from customer behavioral loss mitigation. Presented results to data analytics manager who implemented recommendations from Feed Forward Neural Network/ predictive modeling, and saved $1 million from credit defaults. Collaborated closely with SQL programming teams to produce effective and sustainable working models.Performed customer segmentation modeling using discriminant analysis and multiple regression techniques for campaign response management project. Tested hypothesis and identified the characteristics (age, gender, FIPS etc.) of customers mostly likely to remain company debtor. Prepared and presented detailed visual reports on PowerPoint to implement insights to project directors and data analytics managers. -
Healthcare Fraud Senior Biostatistician/ ResearcherUnitedhealth Group Feb 2005 - Jun 2007UsLed the Analytics Team by recovering 20 Million $ by discovering Fraudulent Billing patterns from statistical models built on SPSS Clementine in Oracle 10G. Demonstrated motivation and innovation for prospective and retrospective insurance fraud recovery productiation. Managed and taught online training and development courses on American Business Models, Applied Statistical Modeling, and Ingenix Chiropractor Healthcare Fraud Matrices to junior statisticians working for UnitedHealth’s offshore subsidiary in India. Created Predictive models such as Decision Tree (CHAID), Neural Net, Logistic Regression, Factor analysis, Bayesian Models, E&M Algorithm, Link Analysis, Clustering and Canonical Correlations to generate healthcare insurance fraud hypothesis and characterize the Fraud Patterns. Hard work led to greater recovery rates and reduced quarterly losses by 15%.Researched new statistical methods or applied combination of methods to uncover previously unknown fraud patterns. Advocated for the use of non-parametric statistical methods such as Wilcoxon’s Rank Test to initiate critical health care utilization and disease management programs. Examined company data extraction processes and implemented innovative SQL queries on the Tool for Oracle Application Developers (TOAD) and applied complex data cleansing techniques on 40 million rows at a time. Communicated extensively with others (Mid-Manager to Executive Vice President) within Organization to reach/build consensus on problems/issues that have arisen and led teams or work groups to meet project goals and deadlines. Received Results Reward from SVP in March 2007 for consistently presenting money saving ($) statistical models for two years. -
Entrepreneur- Senior Statistical Survey ConsultantElance Sep 2004 - Jan 2005Mountain View, Ca, UsCustomer Behavior Profiling (SAS) - Investigated Financial Product Management on Web by SAS EG 3.0 with 1,000 unique survey respondents. The data collected on internet was analyzed by the Cluster, Factor and Discriminant Analysis. These methods uncovered $200,000 potential profit from customers that needed hand holding in the Customer Loyalty program. Segmentation Modeling (SAS) - Provided research question," Do Bank websites have advantage in meeting information needs for financial management of customers over Brokerage firms or Mutual Fund company websites?" Logistic Regression models developed from 800 market research respondents on SAS EG 3.0 indicated that there was 15 times higher odds of female respondents using the Bank websites compared with the male group at low education levels. Customer Segmentation for Channel Strategy of Office Supplier - Conducted the Primary Research, "would the customers of store biased office suppliers migrate to online marketing presence?" Collected data from customer interception in retail environment and Logistic Regression analysis indicated that those customers would indeed involve in multi-Channel shopping behavior. The willingness of several store-biased customers and catalogue purchasers to move to internet was interpreted as existence of a customer segment that would save millions of $ in cost of doing business from those two channels. -
Marketing StatisticianBest Buy Jan 2004 - Jun 2004Richfield, Minnesota, UsCalculated sample size and conducted analysis on Online Market Research data that showed odds of purchasing from Best Buy store by female gender due to "reason for visit" was 6 times higher than male customers. If the model dropped this variable, then there was no difference between these two genders in purchase behavior. I conceptualized this project by asking simple research questions," is there a gender difference in online product purchase from male dominated Best Buy segments" AND "can age, income, life style choices be predicted from online purchases a customer makes for Non-segment products?" I delivered end to end project which resulted in establishment of need for a married female segment first time in Best Buy history. The hypotheses, "more Buzz buy from Buzz stores but Non-buzz stores are more profitable" and "Multiple segment non-buzz stores increases awareness (Trial, purchase) of non-buzz VPE's to Buzz customers with higher satisfaction than single segment non-buzz stores", motivated senior management and analysis of every Best Buy segment demonstrated Female gender or mature preferences of male customers. It eventually resulted in Soccer Mom stores all over USA that now makes at least $1 BILLION for Best Buy every year. Developed Statistical Models to evaluate the effectiveness of Direct Marketing Campaigns. Innovation reward was awarded by the Director of Marketing Analytics for providing this insight.Worked 55-70 hours a week and asked questions to uncover deep sheathed information such as "When and how a Metric under investigation is not just a metric but it is "Behaviorally Adjusted Metric (BAM) for online purchases"? If Ray and Jill buy Buzz products online then % increase in Units/customer and Transaction/customer, be BAM? Is Top BAM customer mutating into Non-BAM customer? Who, When, Why, Where and How? These research questions saved Best Buy $2,000,000 from inventories stored uselessly for Stores and Online purchases. -
Microbiology / Healthcare Six Sigma AnalystDsm Food Specialties Jan 2001 - Dec 2003Heerlen, Limburg, NlUsed Design and Analysis of Experiments and Survival Analysis concepts as relevant to Six Sigma / quality control to Defend DSM Food Specialty products in Journal of Bacteriology research publication. The analytical methods demonstrated that the product defect (Weeping or water seeping out from Cheese) was not due to under-performing DSM bacteria culture and saved Millions $ in litigation costs. Factors causing low bacterial culture quality were analyzed by SAS EG 3.0. First, cheese manufacturing data was collected and stepwise regression was performed. The heteroscendacity of variances indicated likely Multicollinearity in data. Principal Component Regression indicated that the cooling after sterilization variable was highly correlated with factor loadings interpreted as low bacteria nutrient contents. This analysis identified significant bottlenecks in manufacturing process and led to a policy that improved product re-order from customers significantly ($) in B2B Marketing Environment. Developed statistical concepts to analyze the product shelf life of bacteria culture. The specific questions asked were 1. How much batch-to-batch variability is there? 2. How much bacteria cheese culture strength drops in cold storage? 3. Does the bacteria culture looses activity/strength faster if stored at -40*C than -45*c. Analysis of Variance with sampling error showed that batch variation was more significant (P<.05) than storage temperature. Applied Lean manufacturing and Bootstrap concepts that indicated Mean +/-1 Standard Deviation was the only variability related to biological response, thus increasing the precision and accuracy of LAB methods involved in product manufacturing. These methods saved at least $500,000 and models are used companywide in USA and Holland. -
Genomics Data AnalystUtah State University Jul 1997 - Dec 2000Logan, Utah, UsPerformed library research for statistical methods (Generalized Linear Model VS. Expectation and Maximization Algorithm or E&M Algorithm) to analyze Hepatitis C data and, processed the data by E&M Algorithm towards Million $ patent generation in research fund. Mentored Scientists on Cluster Analysis for genetic profiling. Collected and processed MIPS Genomics data for human growth retardation project by Logistic Regression.Sinha, N.K. 1998. Conceptual Models to Characterize Mechanisms and stages of weed invasion into Crops: Research Needs for Sustainable Agriculture. Agronomy J. 38:314.Sinha, N.K., M. Choudhary and U.C. Hymes.1998. Enhanced Weed Tolerance by Crops: A Challenge to Sustainable Agriculture. Agronomy J. 38:68. -
Statistical ConsultantSouth Dakota State University Nov 1993 - Jun 1997Brookings, South Dakota, UsSuccessfully Managed Grant process, Led Predictive Modeling, Tuckey-Duckworth analysis and Fractional Factorial Design of Experiments to test Genetically Modified Organisms (GMO) interaction hypotheses. Three papers were published in reputed, peer reviewed Ecological Genetics journals. Sinha, N.K. and M. Choudhary. 1996. Weed Management by Competitive cultivar: Ecology of Variation and Interaction among natural weed populations. Agronomy J. 36:78Hymes, U.C., J.R. Romans, and N.K. Sinha. 1992. Inability of consumers to differentiate among Frankfurters made with beef, chicken, lamb and pork. J. Animal Science. 70:222.Successfully wrote and received $100,000 grant from retail food industry that saved $300,000/year. That is because Crossover and Nested Design of Experiments to investigate sensitivity of taste panelists found these consumers were not able to differentiate between expensive and low grade Hot dogs. This food company after meeting minimum FDA high grade meat % requirements, successfully replaced the rest of high cost beef meat with that of low cost chicken meat and sold them as Beef Hotdog. These results were published in the peer reviewed Journal of Animal Science. -
Telephone Sales RepresentativeSitel Inc Oct 1993 - May 1997* Achieved 95%, 105% and 115% of the company goal for the year 1994, 1995, and 1996, respectively.* Ranked among top five Inside salespersons (cold calling) for selling banking credit cards in the year 1996-1997.* Worked for 6-11:00 PM schedule after 8 hours day as a scientist for almost four years.* Made Transformational change in personality; from a shy, serious introvert scientist TO Ice-breaker & Deal-maker.
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Genomics/ Biometrics AnalystTuskegee University Apr 1989 - Jan 1992Tuskegee, Alabama, UsLed and published novel Cluster Analysis/ Segmentation of Genomics data for genetic profiling. Interpreted and Presented results in an International ConferenceManaged Graduate and Faculty research data to evaluate complex and critical factors in investigations and recommended solutions. . Taught SAS STAT, one-way, multi-way, repeated measures Design and Analysis of Experiments (ANOVA), and analysis of covariance (ANCOVA) to graduate students.Varadharajan, GS, N.K. Sinha and CS Prakash. 1992. RFLPs and Human DNA Fingerprinting Prediction and Evaluation in Sweet potato. Proceedings of sweet potato 21st Century DNA Technology. 1:92-97Hileman, D.G, Haluka. S, P. Kenjike, N.K. Sinha and P. Biswas.1991. Effects of elevated CO2 and differential watering on Canopy Photosynthesis and Transpiration of field grown cotton. Tuskegee Horizon: 22. Bhattacharya, NC, J.M. McKinnon, G. Gowda, G. Haluka, N.K. Sinha, D.R. Hileman, B.A. Kimball, B. Lynch, A.A. Hosney, M.H. Abdel-Al, M.S. Ismail. 1991. Water Potential of Cotton grown under optimal and limiting levels of water in free air CO2 enriched environment. Proceedings Beltwide Cotton Conferences. 2:834-835.
Navin Sinha, Ms, Mba Skills
Analytics
Data Mining
Predictive Analytics
Data Analysis
Sas
Strategy
Leadership
Predictive Modeling
Business Intelligence
Business Development
Statistical Modeling
Statistics
Management Consulting
Project Management
Program Management
Product Management
Business Analytics
Market Research
Big Data
Segmentation
E Commerce
Sas/sql
Spss
Logistic Regression
Healthcare Consulting
Online Marketing
Competitive Analysis
Change Management
Utilization Management
Data Management
Quantitative Analytics
Time Series Analysis
Customer Insight
Sql
Consumer Insights
Consumer Behavior
Artificial Neural Networks
Neural Networks
Visual Analytics
Temporal Analytics
Product Innovation
Process Improvement
Six Sigma
Cluster Analysis
Consumer Behaviour
Text Mining
Healthcare Reform Analytics
Utility Computing
Decision Trees
Navin Sinha, Ms, Mba Education Details
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University Of Illinois Urbana-ChampaignTomato Genomics -
Rajendra Agricultural UniversityStatistics
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University Of Nebraska-LincolnSpatial Statistics/ Agriculture
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Utah State UniversityDecision Science
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Utah State UniversityFinancial Mathematics
Frequently Asked Questions about Navin Sinha, Ms, Mba
What company does Navin Sinha, Ms, Mba work for?
Navin Sinha, Ms, Mba works for Double Check Consulting
What is Navin Sinha, Ms, Mba's role at the current company?
Navin Sinha, Ms, Mba's current role is Owner and CEO at Double Check Consulting (BPO): #AI 4 #Healthy #Food and #Humans.
What is Navin Sinha, Ms, Mba's email address?
Navin Sinha, Ms, Mba's email address is si****@****ail.com
What is Navin Sinha, Ms, Mba's direct phone number?
Navin Sinha, Ms, Mba's direct phone number is +195290*****
What schools did Navin Sinha, Ms, Mba attend?
Navin Sinha, Ms, Mba attended University Of Illinois Urbana-Champaign, Rajendra Agricultural University, University Of Nebraska-Lincoln, Utah State University, Utah State University.
What are some of Navin Sinha, Ms, Mba's interests?
Navin Sinha, Ms, Mba has interest in Teradata, Spss 13, Applications And Tools, Systat, Clementine 13, Sas Bi 5, Claritas/prizm, Sql Assistant, Business Objects (Webi), Statistixl.
What skills is Navin Sinha, Ms, Mba known for?
Navin Sinha, Ms, Mba has skills like Analytics, Data Mining, Predictive Analytics, Data Analysis, Sas, Strategy, Leadership, Predictive Modeling, Business Intelligence, Business Development, Statistical Modeling, Statistics.
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