Data Scientist

@ Blend360

Company Overview

Blend360 is building a scalable Media Mix Optimization (MMO) solution to help clients maximize marketing investments. The Data Scientist will play a crucial role in integrating statistical rigor with real business impact.

Project Overview: Media Mix Optimization (MMO)

This in-house MMO platform empowers clients with data-driven decision-making in marketing strategy. It applies Bayesian and frequentist methods to quantify channel-level ROI, measure incrementality, and simulate outcomes under various budget scenarios.

Key Components

• Data Integration: Combining diverse datasets into a unified modeling framework.
• Model Development: Building robust media mix models using hierarchical Bayesian regression, regularized regression, and time-series modeling.
• Scenario Simulation: Forecasting outcomes under different budget allocations using simulation algorithms.
• Deployment & Visualization: Developing Streamlit-based interactive dashboards for scenario planning and insights delivery.
• Scalability: Engineering solutions to support multiple clients with varying data complexities.

Responsibilities

• Develop and validate media mix models evaluating marketing effectiveness.
• Engineer end-to-end data pipelines for cleaning and structuring diverse datasets.
• Design and deploy Streamlit interactive dashboards for scenario testing and reporting.
• Conduct exploratory data analysis and advanced feature engineering.
• Implement Bayesian methods, regularization, and time-series analysis to improve models.
• Develop optimization algorithms to recommend strategic budget allocations.
• Collaborate with product, engineering, and client teams to align on solutions.
• Present insights to technical and non-technical stakeholders.
• Stay current with emerging techniques in media mix modeling and marketing science.

Qualifications

• Bachelor’s or Master’s degree in a relevant field (Data Science, Statistics, etc.).
• Proven experience in media mix modeling, marketing analytics, or econometrics.
• Strong proficiency in Python (pandas, NumPy, scikit-learn, statsmodels, PyMC).
• Experience with Streamlit or equivalent frameworks for interactive application development.
• Proficiency in SQL and handling large-scale datasets.
• Excellent communication skills to translate complex models into actionable insights.

Preferred Qualifications

• Experience with Bayesian hierarchical models and time-series decomposition.
• Familiarity with cloud platforms (AWS, GCP, Azure) and big data ecosystems (Spark, Hadoop).
• Knowledge of advanced visualization tools like Tableau, Power BI, or Plotly.
• Understanding of causal inference techniques and marketing attribution methods.

Key skills/competency

• Data Scientist
• Media Mix Modeling
• Statistical Modeling
• Python
• Streamlit
• Marketing Analytics
• SQL
• Bayesian Methods
• Machine Learning
• Data Integration