Data Scientist
Data Scientist
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Salary Not Disclosed
1 Vacancy
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 :
Bachelors or Masters degree in Data Science Statistics Computer Science Applied Mathematics or related field.
Proven hands-on experience in media mix modeling marketing analytics or econometrics.
Strong proficiency in Python and key data science libraries (pandas NumPy scikit-learn statsmodels PyMC or similar Bayesian frameworks).
Experience with Streamlit or equivalent frameworks (Dash Shiny) for building data- driven applications.
Proficiency in SQL for querying joining and optimizing large-scale datasets.
Solid foundation in statistical modeling regression techniques and machine learning.
Strong problem-solving skills with the ability to structure ambiguous business problems
into data-driven solutions.
Excellent verbal and written communication skills to translate technical outputs into
business decisions.
Preferred Qualifications
Experience with Bayesian hierarchical models time-series decomposition and marketing attribution approaches.
Familiarity with cloud-based platforms (AWS GCP Azure) for data processing model training and deployment.
Experience with data visualization tools beyond Streamlit (Tableau Power BI Plotly).
Exposure to big data ecosystems (Spark Hadoop) for large-scale data processing.
Knowledge of causal inference techniques (propensity scoring uplift modeling geo-
experiments).
Remote Work :
Yes
Employment Type :
Full-time
Employment Type
Remote
Company Industry
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
