Overview :
This role requires the person to understand business problems & existing data structures, contribute to designing, proposing & building solutions, and be hands-on on the technical front in building the solutions including building Machine Learning algorithms and other implementation frameworks as required. The Senior Scientist is expected to be a very hands-on technical person having built models and implemented them in production environments for business' consumption. This role is primarily for Marketing Analytics activities including but not limited to building Market-Mix & Attributions models and Digital Marketing Analytics.
Role & Responsibilities:
- Work with the Data Science & Business teams to understand key objectives & challenges and participate in framing requirements and designing solutions.
- During solution design stage, keep an eye on existing data available for building models and maintain clarity about how they would be implemented & applied.
- Work with different teams to collate data from HubSpot, Salesforce, Google Analytics or other digital platforms to build such solutions. Also, identify and harvest relevant external data for marketing activities.
- Contribute to generating ways to harvest data generated from experiments with an objective to use them in exercises. This will require the collated data to be structured, usable & maintained for future use.
- Be technically good in building models & data management.
- Be a subject matter expert on Digital Marketing, Optimizing Budget by Channel & Attribution modelling.
- Work on Online & Offline marketing challenges including SEO & SEM and using such data to design & develop solutions and recommending actionable.
- Execute tasks on technical front and collaborate with members of the team on the same.
Required Profile:
- Has worked on different Marketing Analytics Projects like Customer Acquisition & Retention, Churn identification, CLTV, Market Mix & Attribution Modelling etc.
- Be proficient in different modelling techniques including but not limited to Linear & Logistic regression, Random Forest, XGBoost, Chaid trees, survival modelling etc. using Python, R, SAS, Power BI or other tools as may be required.
- Should have good communication skills and be able to articulate and present ideas or work to members of the team, Senior Management and key stakeholders and support functions.
- Has had at least 5-8 years' experience in working on different modelling exercises.
- Has a degree in engineering from an institution of repute - preferably from the IITs or NITs or a degree in statistics or economics.
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