Data Scientist

Wildnet Technologies; Dadri; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Wildnet Technologies seeks a Marketing Analytics specialist to build MMMs, Bayesian models, and causal inference solutions. You will forecast, perform experimentation, and craft dashboards for business insights. Collaboration with cross-functional teams to translate analyses into optimized marketing strategies is essential.

The role emphasizes quantitative rigor, scalable Python workflows, and transparent communication of model assumptions and limitations to stakeholders.

Qualifications

• 3–6 years in Marketing Analytics or related fields.
• Experience in agency/consulting or digital marketing analytics.

Responsibilities

• Develop, implement, and optimize MMMs to measure marketing impact.
• Build Bayesian models for forecasting and scenario planning.
• Apply causal inference to quantify campaign impact.
• Design advanced statistical modelling including time-series.
• Create attribution frameworks using experimental data.
• Run A/B tests and geo experiments with lift analysis.
• Analyze large marketing datasets for insights.
• Develop dashboards in Power BI or Looker Studio.
• Collaborate with data science, engineering, and business teams.
• Build Python analytics pipelines for model development and reporting.
• Present findings with clear explanations of assumptions and limits.

Skills

Marketing Mix Modeling

MMM

Bayesian

Bayesian Inference

PyMC

PyMC3

Statistical Modeling

Econometrics

Causal Inference

Incrementality

Regression

Statsmodels

Meridian

Google Meridian

LightweightMMM

Robyn

Geo Lift

Python

SQL

Power BI

Looker Studio

Tools

Python

Pandas

NumPy

SciPy

scikit-learn

PyMC

Statsmodels

SQL

Power BI

Looker Studio

Meridian

BigQuery

Vertex AI

Docker

MLflow

Job description

Job Description

Key Responsibilities

• • Develop, implement, and optimize Marketing Mix Models (MMM) to measure the impact of marketing investments across channels and support budget allocation decisions.
  • Build robust Bayesian statistical models for marketing effectiveness, forecasting, uncertainty estimation, and scenario planning.
  • Apply causal inference methodologies to measure the incremental impact of marketing campaigns and distinguish correlation from causation.
  • Design and execute advanced statistical modelling techniques including regression analysis, hierarchical Bayesian models, time-series analysis, and probabilistic modelling.
  • Develop attribution and incrementality measurement frameworks using experimental and observational data.
  • Conduct hypothesis-driven experimentation, including A/B testing, geo experiments, holdout testing, and lift measurement.
  • Analyze large-scale marketing and media datasets to generate actionable business insights.
  • Build automated dashboards and reporting solutions using Power BI or Looker Studio.
  • Collaborate with Data Science, Engineering, Media Strategy, and Business teams to translate analytical findings into marketing optimization strategies.
  • Build scalable Python-based analytics pipelines for model development, validation, monitoring, and reporting.
  • Present statistical findings and business recommendations to stakeholders with clear explanations of assumptions, confidence intervals, and model limitations.

Required Skills

Experience

• • 3-6 years of experience in Marketing Analytics, Marketing Science, Applied Data Science, Econometrics, or Media Analytics.
  • Strong experience working in agency, consulting, or digital marketing analytics environments.

Core Technical Skills

• • Expert knowledge of Marketing Mix Modelling (MMM).
  • Strong understanding of Bayesian Inference and Bayesian statistical techniques.
  • Strong expertise in Statistical Modelling including:
  • Linear Regression
  • Multivariate Regression
  • Hierarchical Models
  • Time-Series Models
  • Econometric Modelling
  • Hands-on experience with Causal Inference methodologies such as:
  • Difference-in-Differences
  • Synthetic Control
  • Propensity Score Matching
  • Instrumental Variables
  • Uplift Modelling
  • Strong Python programming skills using:
  • pandas
  • NumPy
  • SciPy
  • scikit-learn
  • PyMC / PyMC3
  • Statsmodels
  • Strong SQL skills.
  • Experience with Power BI or Looker Studio.

Preferred Skills

• • Experience with Google Meridian Marketing Mix Modeling Framework.
  • Experience building Bayesian MMM models using Meridian.
  • Knowledge of GeoLift, LightweightMMM, Robyn, or other modern MMM frameworks.
  • Experience with GCP, BigQuery, Vertex AI, or cloud-based analytics platforms.
  • Knowledge of MLflow, Airflow, Docker, and CI/CD.
  • Familiarity with Generative AI for reporting automation and insight generation.

Must-Have Keywords for Screening

• • Marketing Mix Modeling
  • MMM
  • Bayesian
  • Bayesian Inference
  • PyMC
  • PyMC3
  • Statistical Modeling
  • Econometrics
  • Causal Inference
  • Incrementality
  • Regression
  • Statsmodels
  • Meridian
  • Google Meridian
  • LightweightMMM
  • Robyn

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.