Find The RightJob.
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
Salary Range:
$50,000 – $180,000 USD / year
(Commensurate with location and experience)
Remote Friendly:
Work from where you are most productive.
Learning Budget:
Stipend for data courses (Coursera, DataCamp) and books.
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