Loveesh Bhatt Email & Phone Number

Hyderabad, Telangana, India

India

Pune, Maharashtra

Pune Area, India

Pune

Maersk Gsc Powai Mumbai

Part of the cost leadership initiative being undertaken at Maersk Tankers. Day to day tasks involve using advanced statistical techniques to find and remove operational inefficiencies for process improvement and cost optimization. Currently based at Maersk GSC Powai office • Gathering stakeholder requirement• Doing complex analysis using the vessel’s daily operational data to recommend processes that improve cost efficiency• Building models using multivariate regression, applying… Show more Part of the cost leadership initiative being undertaken at Maersk Tankers. Day to day tasks involve using advanced statistical techniques to find and remove operational inefficiencies for process improvement and cost optimization. Currently based at Maersk GSC Powai office • Gathering stakeholder requirement• Doing complex analysis using the vessel’s daily operational data to recommend processes that improve cost efficiency• Building models using multivariate regression, applying machine learning concepts to make better predictions using more refined and accurate models• Liaising with the BI team to recommend changes and improvements in the BI data• Created a tool called DRC Estimator using VBA and R to predict changing operational expenses due to changing trade area, vessel age and the segment of the vessel.• Training a team of analysts from Fuel Optimization on R statistical software and imparting best practices for model building • Using visualization tools like Power BI, QlikView & Qliksense to provide stakeholders with relevant insights to help them take informed day to day decisions• Building control charts for various vessels using R statistical software and historical data to track and monitor processes going out of control• Recommending better practices using insights from data and technical superintendents handling vessels to improve process efficiencies• Submitting kaizens frequently to reduce dependence on FTE & automating tasks Show less

Santacruz Mumbai

• Creating predictive models using logistic regression to reduce subscriber churn• Trend analysis to determine the root cause for dip in data usage for various circles as and when required• Implementing Kaizen and continuous process improvement to segment data for the Data IRIS team using K-Means clustering algorithm• Conceptualizing and automating the management data dashboard used for daily business KPI tracking for senior management• Publishing monthly trackers and reports… Show more • Creating predictive models using logistic regression to reduce subscriber churn• Trend analysis to determine the root cause for dip in data usage for various circles as and when required• Implementing Kaizen and continuous process improvement to segment data for the Data IRIS team using K-Means clustering algorithm• Conceptualizing and automating the management data dashboard used for daily business KPI tracking for senior management• Publishing monthly trackers and reports for the Data team to take strategic decisions and formulating go to market strategies• Managing communications and development of collaterals aimed at addressing churn. Show less

Bkc Mumbai

-Designing algorithms for team selection on the basis of player performance metrics.-Building predictive modelling techniques and business models using raw data/primary research to help the organization reduce the future risk and implement a better strategy on the concerned project.-Using social media analytics and algorithms to derive insights for effective marketing of the Sahara Polo Warriors team through various social media and online channels.-Communicate complex quantitative… Show more -Designing algorithms for team selection on the basis of player performance metrics.-Building predictive modelling techniques and business models using raw data/primary research to help the organization reduce the future risk and implement a better strategy on the concerned project.-Using social media analytics and algorithms to derive insights for effective marketing of the Sahara Polo Warriors team through various social media and online channels.-Communicate complex quantitative analysis in a clear, precise, and actionable manner for the organization to take informed decisions-Create and oversee development of presentations, making collateral and online content-Develop campaigns and sales opportunities through data driven research to enhance and build the organizations ROI.-Project planning and development including 5 year revenue projections, P&L as well as NPV Analysis and Return on Investment for a major CSR project on the anvil, The Sahara Sports Foundation which aims to develop various Olympic sporting disciplines at the grass root level. -Inviting sponsorships for major events through various associations and presenting them with the whole event and the budget related to it. Show less

Bkc Mumbai

Project: Research on fixing Home Sale Price Determination on the basis of facilities providedContributed on the research involving the Determination of Home Sale Price(Dependent Variable) for a Premier Luxury Township called "Qing and Quest" with the help of the a data set of 1000 data points collected across the premier luxury townships and project across India collected and cleaned(na or missing values removed) from the research reports of Knight Frank India. The Built Up Area (Sq… Show more Project: Research on fixing Home Sale Price Determination on the basis of facilities providedContributed on the research involving the Determination of Home Sale Price(Dependent Variable) for a Premier Luxury Township called "Qing and Quest" with the help of the a data set of 1000 data points collected across the premier luxury townships and project across India collected and cleaned(na or missing values removed) from the research reports of Knight Frank India. The Built Up Area (Sq. Foot) was the key predictor variable. The Regression model was ran using other independent variables like Median Neighborhood Income, Age of the home, Size of the overall plot(if applicable), Quality of local schools, Quality of the hospitals around, Total Free space, No. of recreational facilities such as swimming pools, gymnasium, snooker and pool, crèche area, spa and sauna, children’s play area, meditation center, Availability of concierge services. All the predictor variables except the first three variables mentioned above were categorical variables ranked on a scale of 1 to 7, 7 being the best. On running the data visualization for the regression model the data was found to be nonlinear and the liner regression model didn't fit the test anymore. A two degree polynomial regression equation with the key predictor variable "size of the plot" was represented as a variable having a degree of 2 in the polynomial equation. The new regression model helped determine the Home sale price of a township based on various facilities that the client wanted to provide in the project and hence communicated the overall budget of the project through NPV and Cash Flow analysis. Show less

Mumbai Area, India

Project: Consumer Behavior Mapping using Predictive/Regression ModellingDid exploratory and confirmatory data analysis to find a relation between the purchase behavior of consumers vis a vis independent variables like time spent at a luxury store, brand exposure, social media engagement, uniqueness, aesthetics & price for luxury brandsProvided insight into a regression/predictive linear modelling model to predict the value of the Sales(Dependent Variable) having a significant… Show more Project: Consumer Behavior Mapping using Predictive/Regression ModellingDid exploratory and confirmatory data analysis to find a relation between the purchase behavior of consumers vis a vis independent variables like time spent at a luxury store, brand exposure, social media engagement, uniqueness, aesthetics & price for luxury brandsProvided insight into a regression/predictive linear modelling model to predict the value of the Sales(Dependent Variable) having a significant relationship with the No. of Footfalls across a sample of 400 data points with a significance level of 95% and a confidence interval of 90-95%. Some of the other predictor variables that had a significance on the performance of dependent variable as well as some interaction with the key predictor variable were Brand Exposure : High or low(Categorical Variable),Time spent at the store (variable causing hetroskadasticity), Price, Social Media Engagement : High or Low(Categorical Variable), Personalized Service(Categorical Variable), Ease of access (variable causing interaction with the key predictor variable), Payment Option(Categorical Variable), Delivered at home, in parking, personal(Categorical Variable). All the categorical variables and the variables causing interaction amongst themselves where represented as dummy variables in the regression model. Hetroskadastic data was dealt with the help of a Variance Co-variance Matrix that helped in the next iteration of the regression model to predict the independent variable(Time spent at the store) having a non-significant relationship with the dependent variable(Sales). The overall research helped the client to develop a digital media campaign and a marketing strategy based on how the consumers interact with the luxury brands. Show less