Data Scientist — Analytics roles draw analytical talent hunting for roles.

About the Role We believe that the best decisions are backed by data. We are seeking a curious and analytical Data Scientist to champion our data-driven culture.

In this role, you will act as a bridge between technical data and business strategy. You will mine massive datasets, build predictive models, and—most importantly—tell the story behind the numbers to help our leadership team make smarter choices. You are perfect for this role if you are as comfortable with SQL queries as you are with slide decks.

### What You Will Do

• Exploratory Analysis: Dive deep into raw data to discover trends, patterns, and anomalies that others miss.
  

• Predictive Modeling: Build and test statistical models (Regression, Time-series, Clustering) to forecast business outcomes and customer behavior.
  

• Data Visualization: Create clear, impactful dashboards using Tableau, PowerBI, or Python libraries (Matplotlib/Seaborn) to visualize success metrics.
  

• Experimentation: Design and analyze A/B tests to optimize product features and marketing campaigns.
  

• Data Cleaning: Work with Data Engineers to clean and structure messy data for analysis.
  

• Strategy: Present findings to stakeholders, translating complex math into clear, actionable business recommendations.
  

  
  
  
  

• Experience: 2+ years of experience in Data Science or Advanced Analytics.
  

• The Toolkit: Expert proficiency in Python or R for statistical analysis.
  

• Data Querying: Advanced SQL skills are non-negotiable (Joins, Window Functions, CTEs).
  

• Math Mindset: Strong grasp of statistics (Hypothesis testing, distributions, probability).
  

• Visualization: Ability to communicate data visually using Tableau, PowerBI, or Looker.
  

• Communication: Excellent verbal and written skills; you can explain a p-value to a non-technical manager.
  

### Preferred Tech Stack (Keywords)

• Languages: Python (Pandas, NumPy), R, SQL
  

• Viz Tools: Tableau, PowerBI, Looker, Plotly
  

• Machine Learning: Scikit-learn, XGBoost (applied to business problems)
  

• Big Data: Spark, Hadoop, Snowflake