Data Scientist

Data Scientist – Price Optimization & Churn Forecasting Fully Remote Compensation: $65/Hour W2 Oil/Energy Overview We are seeking a Data Scientist with approximately 2–3 years of experience who combines strong technical capabilities with the ability to work closely with business stakeholders. This role is ideal for someone who enjoys learning through hands-on analytics and modeling while directly influencing business strategy and financial outcomes. The Data Scientist will apply machine learning and analytics to solve real-world retail and customer-focused problems, helping business partners make more informed and profitable decisions. Key Responsibilities • Embrace a culture of humility, curiosity, and measurable impact • Process and analyze large datasets using Python, PySpark, and Databricks • Develop predictive models, analytical frameworks, and data-driven dashboards • Perform hands-on analytics and modeling while continuously learning and expanding domain expertise • Translate customer and prospect insights into actionable recommendations for business partners • Support decision-making related to customer behavior, revenue growth, and profitability Required Qualifications Machine Learning & Analytics • Proven experience applying machine learning to solve business problems • Ability to clearly explain the business use cases for ML models (e.g., customer churn, forecasting, personalization, pricing, or segmentation) Retail & Customer Analytics Experience • Prior experience in a retail or consumer-focused environment, with exposure to one or more of the following areas: • Customer churn and retention analysis • Profit and margin optimization • Pricing and promotional strategies • Subscription or recurring-revenue models • Customer loyalty, engagement, and lifecycle analysis • Sales growth and demand forecasting initiatives Data Science for Business Impact • Demonstrated ability to use data science to improve customer experience and drive measurable business outcomes • Experience translating analytical insights into recommendations that influence strategy and operations Technical Skills • Strong proficiency in Python and common data science libraries, including: • PySpark, NumPy, pandas • scikit-learn, XGBoost • Matplotlib, lifelines • Experience working with modern data platforms such as Databricks Communication & Collaboration • Strong cross-functional communication skills, with the ability to partner effectively with product, marketing, analytics, and business teams • Comfortable presenting insights to both technical and non-technical audiences in a clear and persuasive manner Ideal Candidate Profile • Early-career Data Scientist eager to grow through hands-on work • Equally comfortable working with code, data, and business requirements • Curious, collaborative, and motivated by real-world impact rather than purely theoretical modeling