Data Scientist

Job Title: Data Scientist

Overview

We are seeking a highly skilled Data Scientist to join our marketing analytics organization

In this role, you will leverage statistical modeling, machine learning, and data engineering techniques to deliver insights, build predictive models, and support data driven decision making across the business conducting ad-hoc analysis

The ideal candidate is analytically strong, curious, and comfortable working with large datasets and modern data technologies

Key Responsibilities

Analytics Modeling (40%)

Build, validate, and deploy machine learning models (classification, regression, forecasting, clustering, NLP, etc)

Conduct statistical analyses and A/B tests to evaluate business performance and product changes

Translate ambiguous business questions into structured analytical problems

Data Engineering Preparation (10%)

Acquire, clean, and manipulate large datasets from multiple sources

Build reproducible data pipelines using Python, SQL, and Snowflake

Work closely with data engineers to optimize data structures and improve data availability

Insights Business Impact (40%)

Deliver clear, actionable insights to stakeholders through ah-hoc analysis, dashboards, visualizations, and written summaries

Partner with product, marketing, finance, and operations teams to identify opportunities for optimization

Support KPI development and help teams understand business trends

Model Deployment Monitoring (10%)

Collaborate with engineering teams to deploy models into production environments

Monitor model performance and retrain/adjust, as necessary

Maintain documentation, reproducibility, and version control of all modeling work

Required Skills Qualifications

Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field

3 7+ years of experience applying data science techniques in a business environment

Proficiency in Python (pandas, scikit learn, NumPy, statsmodels) or other model building tools

Strong SQL skills and experience with relational or cloud databases

Deep understanding of statistical modeling, hypothesis testing, and experiment design

Experience with machine learning , feature engineering, and model evaluation

Ability to communicate complex concepts to non technical audiences

Ability to perform ad-hoc analysis for LOBs

Preferred Qualifications

Experience with cloud platforms such as Snowflake, Azure, AWS, or GCP

Experience with big data tools (Spark, Databricks, Snowflake, BigQuery, Redshift)

Experience with deep learning (PyTorch, TensorFlow) or NLP

Experience building dashboards in Power BI, Tableau, or similar tools

Experience as a data analyst conducting ad-hoc analysis

Knowledge of data governance and model lifecycle best practices

Soft Skills

Strong problem solving and critical thinking skills

Comfort working in fast paced, ambiguous environments

Curiosity and a continuous learning mindset