Data Science With Cltv

Role &Amp; Responsibilities :

- A Business Facing Role That Requires Collaborating With Senior Business Leaders, To Understand Key Portfolio Objectives &Amp; Challenges.

- Work With Senior Leaders Within The Data Science Function For The Above, To Frame Business Requirements And Design Required Solutions.

- While Designing Solutions, Keep An Eye On Implementation &Amp; Application Of Machine Learning Algorithms Being Built.

- Work With Different Teams To Collate Data From Hubspot &Amp;/Or Salesforce To Build Such Solutions.

- Design Experiments Where Required And Frame Means To Harvest Data Generated From Such Experiments With An Objective To Use Them In Exercises.

- Be Technically Good In Building Models &Amp; Data Management.

- Has Strong Communication Skills And Is Able To Articulate And Present Ideas Or Work To Senior Management And Key Stakeholders, As Well As Colleagues And Support Functions.

- Take Lead In Executing Tasks On Technical Front And Mentor / Guide Junior Members Of The Team On The Same.

- Be A Subject Matter Expert On Customer Lifetime Value Works And Preferably Have Some Knowledge Of Market-Mix Modelling And Customer Acquisition &Amp; Retention.

- Work On The Subject At Both A Portfolio Level As Well As At A Customer Level With An Intent To Using Them In Conjunction With Other Streams Like Acquisition &Amp; Market-Mix Works.

- Has A Good Understanding Of Economics Behind Lifetime Value Calculations And Acquisition &Amp; Retention.

- Manage Team On Day-To-Day Activities Including Planning &Amp; Allocating Tasks As Required In Collaboration With Senior Leaders.

Required Profile :

- Has Worked Extensively On Cltv Challenges Using Data Science, Preferably For The Financial Services Industry.

- Has Had Exposure To Collaborating With Teams Distributed Across Geographies &Amp; Time-Zones.

- Has Worked On Cltv At Both A Portfolio Level As Well As At A Customer Level.

- Has Good Exposure To Hubspot, Salesforce Environments.

- Be Proficient In Different Modelling Techniques Including But Not Limited To Linear &Amp; Logistic Regression, Random Forest, Xgboost, Chaid Trees, Survival Modelling Etc. Using Python Or Other Tools As May Be Required.

- Has Had At Least 2-4 Years' Experience In Managing Teams With A Total Experience Of 5-8 Years.

- Has A Degree In Engineering From An Institution Of Repute - Preferably From The Iits Or Nits Or Has A Degree In Economics Or Statistics From An Institution Of Repute.