Data Scientist

Blend360 India

0 - 5 years

2 - 7 Lacs

hyderabad

Posted:4 hours ago| Platform:

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Skills Required

computer science data analysis product engineering simulation gcp data processing econometrics marketing strategy sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Project Overview: Media Mix Optimization (MMO)

Our MMO platform is an in-house initiative designed to empower clients with data-driven decision-making in marketing strategy. By applying Bayesian and frequentist approaches to media mix modeling, we are able to quantify channel-level ROI, measure incrementality, and simulate outcomes under varying spend scenarios.

Key components of the project include:

Data Integration: Combining client first-party, third-party, and campaign-level data across digital, offline, and emerging channels into a unified modeling framework.
Model Development: Building and validating media mix models (MMM) using advanced statistical and machine learning techniques such as hierarchical Bayesian regression, regularized regression (Ridge/Lasso), and time-series modeling.
Scenario Simulation: Enabling stakeholders to forecast outcomes under different budget allocations through simulation and optimization algorithms.
Deployment & Visualization: Using Streamlit to build interactive, client-facing dashboards for model exploration, scenario planning, and actionable recommendation delivery.
Scalability: Engineering the system to support multiple clients across industries with varying data volumes, refresh cycles, and modeling complexities.

Responsibilities

Develop, validate, and maintain media mix models to evaluate cross-channel marketing effectiveness and return on investment.
Engineer and optimize end-to-end data pipelines for ingesting, cleaning, and structuring large, heterogeneous datasets from multiple marketing and business sources.
Design, build, and deploy Streamlit-based interactive dashboards and applications for scenario testing, optimization, and reporting.
Conduct exploratory data analysis (EDA) and advanced feature engineering to identify drivers of performance.
Apply Bayesian methods, regularization, and time-series analysis to improve model accuracy, stability, and interpretability.
Implement optimization and scenario-planning algorithms to recommend budget allocation strategies that maximize business outcomes.
Collaborate closely with product, engineering, and client teams to align technical solutions with business objectives.
Present insights and recommendations to senior stakeholders in both technical and non- technical language.
Stay current with emerging tools, techniques, and best practices in media mix modeling, causal inference, and marketing science.

Qualifications

Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Applied Mathematics, or related field.
Proven hands-on experience in media mix modeling, marketing anal

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