Full time Marketing Mix Modeler Required (Indians Only)
Budget: ₹750 – ₹1,250 INR
Inviting applications for the role in Statistical Modeling
Responsibilities
· Data preparation and validation :
ü Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.
ü Evaluate the statistical methods and procedures used to obtain data in order to ensure validity, applicability, efficiency, and accuracy.
ü Identify relationships and trends in data, as well as any factors that could affect the results of the model.
ü Using these techniques to identify the transfer function (adstock ,adbank or hills function). of the various media variables on Target by controlling multicollinearity,
· Tools used for analysis :
ü Processing large amounts of data using basic SQL queries.
ü Running statistical models or/and machine learning algorithms using R/ /SAS/Python (expert in two of them is a must)
ü Hands On experience on Dataiku is a plus
· Techniques typical used for analysis are :
ü Simple and Multiple Linear Regression ,
ü Classification such as Logistic Regression and Discriminant Analysis
ü Bayesian Regression using MCMC
ü Resampling Methods such as Bootstrapping and Cross-Validation
ü Dimension Reduction such as principal component regression and factor analysis
· Client Communicate :
ü Communicate results to stakeholders in requested format such as graphs, charts, and tables.
ü Adapt statistical methods to provide end to end business solution
In this role, the candidate may have to at times work during global hours in order to connect with other teams working in different time zones.
Qualifications
Minimum qualifications
A Master's or degree in applied quantitative discipline (e.g. Economics, Statistics, Mathematics, Computational Science)
Preferred skills:
7-10 years’ experience in analytics
Have hands-on experience in development of models using statistical techniques.
Proficiency in software/applications – R/SPSS /SAS/Python (Desirable)
Strong client management and communication skills – written & verbal.
Ability to work independently
Responsibilities
· Data preparation and validation :
ü Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.
ü Evaluate the statistical methods and procedures used to obtain data in order to ensure validity, applicability, efficiency, and accuracy.
ü Identify relationships and trends in data, as well as any factors that could affect the results of the model.
ü Using these techniques to identify the transfer function (adstock ,adbank or hills function). of the various media variables on Target by controlling multicollinearity,
· Tools used for analysis :
ü Processing large amounts of data using basic SQL queries.
ü Running statistical models or/and machine learning algorithms using R/ /SAS/Python (expert in two of them is a must)
ü Hands On experience on Dataiku is a plus
· Techniques typical used for analysis are :
ü Simple and Multiple Linear Regression ,
ü Classification such as Logistic Regression and Discriminant Analysis
ü Bayesian Regression using MCMC
ü Resampling Methods such as Bootstrapping and Cross-Validation
ü Dimension Reduction such as principal component regression and factor analysis
· Client Communicate :
ü Communicate results to stakeholders in requested format such as graphs, charts, and tables.
ü Adapt statistical methods to provide end to end business solution
In this role, the candidate may have to at times work during global hours in order to connect with other teams working in different time zones.
Qualifications
Minimum qualifications
A Master's or degree in applied quantitative discipline (e.g. Economics, Statistics, Mathematics, Computational Science)
Preferred skills:
7-10 years’ experience in analytics
Have hands-on experience in development of models using statistical techniques.
Proficiency in software/applications – R/SPSS /SAS/Python (Desirable)
Strong client management and communication skills – written & verbal.
Ability to work independently