Data Scientist (Retail Focus) – Fully Remote | $65/hour W2
Domain: Oil/Energy
Our client, a leading company in the energy sector, is seeking a Data Scientist to join their team. This role offers an exciting opportunity to leverage both technical and business skills to drive insights, improve customer experiences, and support strategic initiatives.
Role Overview:
The Data Scientist will perform hands-on analytics and modeling to help business partners make data-driven decisions. This is an early-career opportunity ideal for candidates with 1–3 years of experience in data analysis or related fields who are eager to grow their expertise in a retail-focused environment.
Key Responsibilities:
- Embrace a culture of humility, curiosity, and impact.
- Process and manipulate data using Python, PySpark, and Databricks.
- Develop predictive models, dashboards, and analytical solutions.
- Apply machine learning techniques to real-world business problems.
- Translate insights into actionable recommendations for business partners, focusing on customer and prospect behavior.
- Collaborate cross-functionally to support marketing, product, and analytics initiatives.
Required Skills and Qualifications:
- 0–3 years of experience in data analysis, analytics, or related fields.
- Master’s degree in a quantitative discipline or equivalent practical experience.
- Proficiency in Python and relevant packages: PySpark, NumPy, pandas, scikit-learn, XGBoost, Matplotlib, lifelines.
- Strong understanding of applying machine learning to business challenges such as customer churn, forecasting, personalization, or sales growth.
- Experience in a retail environment or exposure to business modeling, including:
- Customer churn & retention
- Profit/margin improvement
- Pricing strategies
- Subscription models
- Customer loyalty and engagement
- Excellent communication skills with the ability to translate technical insights into business impact.
Preferred Qualifications:
- Experience using data science to drive business profitability and enhance customer experience.
- PhD or advanced degree in a quantitative discipline.
- Knowledge of statistical and machine learning methods including frequentist/Bayesian statistics, forecasting, optimization, causal inference, and natural language processing.
- Familiarity with version control systems and cloud-based data operations.
- Strong cross-functional collaboration skills with persuasive and informative communication.
Working Conditions:
- Fully remote, providing flexibility and work-life balance.
This role offers an opportunity to grow professionally while contributing to meaningful business impact in a retail-focused environment.
