Sr. Data Scientist - Commercial

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The Sr. Data Scientist- Commercial is responsible for designing, developing, deploying, and optimizing advanced analytics, machine learning, and decision science solutions that drive commercial growth, revenue optimization, and data-driven decision-making across the U.S. Commercial organization.

The role applies predictive, prescriptive, and optimization techniques to improve pricing strategy, customer segmentation, sales effectiveness, forecasting accuracy, customer retention, and overall commercial performance.

Working closely with Commercial Leadership, Pricing, Sales, Marketing, Finance, and Business Intelligence teams, this position transforms complex business challenges into scalable analytical solutions and actionable insights. The role supports the full analytics lifecycle, including data acquisition, preparation, feature engineering, model development, validation, deployment, monitoring, governance, and continuous improvement.

The Data Scientist also partners with stakeholders to operate analytical solutions through automation workflows, dashboards, and decision-support tools that enable measurable business impact.

Success in this role is demonstrated through improved commercial outcomes, enhanced forecasting capabilities, greater operational efficiency, and increased adoption of data-driven decision-making across the organization.Key Accountabilities:

Advanced Analytics & Machine Learning* Develop, validate, deploy, and optimize predictive, prescriptive, and optimization models that support commercial and strategic business objectives using advanced statistical analysis, machine learning, and AI techniques.

• Build analytical models for forecasting, pricing and elasticity analysis, customer segmentation, propensity modeling, opportunity scoring, resource allocation, and scenario planning to drive data-informed business decisions.
• Perform feature engineering, model selection, training, testing, validation, backtesting, and performance monitoring while evaluating emerging analytical methodologies and technologies to enhance model effectiveness and business value.

Data Engineering & Preparation* Acquire, integrate, cleanse, and transform data from multiple internal and external sources while designing, developing, and maintaining scalable Dataiku workflows, Python pipelines, and SQL processes leveraging Snowflake and enterprise data platforms.

• Ensure data quality, reproducibility, scalability, and governance across analytical environments by applying version control, development best practices, and collaborative processes that support efficient model development and deployment.

Model Deployment & Lifecycle Management* Support the end-to-end deployment of machine learning and analytical solutions using Dataiku automation, Snowflake processes, and modern MLOps practices while monitoring model performance, accuracy, drift, stability, and business impact through established governance frameworks.

• Coordinate model retraining, optimization, and continuous improvement activities while maintaining comprehensive model documentation, validation records, and model cards throughout the model lifecycle.

Business Insights & Decision

Support* Translate complex analytical outputs into actionable business recommendations by identifying trends, risks, opportunities, and performance drivers through advanced analytics and exploratory data analysis.

• Develop analytical frameworks that support strategic planning, pricing, forecasting, and sales effectiveness, while measuring and communicating business value through KPI trees, lift analyses, ROI scorecards, and performance metrics.

Visualization & BI Integration* Collaborate with the Sales Support Business Intelligence team to embed predictive and prescriptive insights into dashboards, reporting tools, and decision-support platforms.

• Develop intuitive visualizations and analytical storytelling approaches for technical and non-technical audiences.

Cross-Functional Collaboration* Partner with cross-functional teams to identify analytics-driven improvement opportunities, gather business requirements, and develop scalable data science solutions that support strategic business objectives.

• Present analytical findings and provide subject matter expertise in advanced analytics and machine learning to stakeholders across all organizational levels, enabling informed decision-making and strategic initiatives.

Skills/Qualifications:

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative discipline.
• Master's degree in Data Science, Analytics, Statistics, Computer Science, or a related field preferred.
• 4+ years of applied experience in data science, machine learning, advanced analytics, or decision science roles.
• Demonstrated experience developing and deploying predictive and prescriptive models in a business environment.
• Experience supporting commercial, pricing, marketing, customer analytics, forecasting, or revenue optimization initiatives preferred.
• Proficiency in Python, including pandas, NumPy, scikit-learn, TensorFlow, PyTorch, or equivalent machine learning frameworks.
• Advanced SQL skills with experience working in Snowflake or similar cloud-based data platforms.
• Hands-on experience with Dataiku or comparable analytics and machine learning platforms.
• Experience utilizing Git, version control processes, and collaborative software development practices.
• Familiarity with MLFlow, CI/CD pipelines, MLOps frameworks, model monitoring, and drift detection methodologies.
• Experience integrating predictive outputs into Power BI, Tableau, or other business intelligence platforms.
• Strong knowledge of statistical analysis, forecasting, segmentation, predictive modeling, optimization, simulation, and experimental design methodologies.
• Ability to translate complex analytical concepts into business-focused insights and recommendations.
• Strong problem-solving, critical thinking, and data storytelling capabilities.
• Excellent communication and stakeholder management skills with the ability to influence both technical and non-technical audiences.
• Strong documentation, governance, and project management capabilities.

Employee Benefits & Incentives

DHL Express benefits and incentive offerings are designed to reflect a substantial experience for both employees and their dependents during their career and life journey. The specifics will vary, but wherever you join and in whatever role, you'll find our benefits and rewards are among the best in the industry They include:

• Competitive Pay
• Bonus/Incentive Programs
• Retirement Savings – 401K with company match
• Medical, Dental, Vision, well-being programs
• Tuition Reimbursement
• Generous Paid Time Off – Starting at 4 Weeks (PT/FT)
• Paid Leave
• Employee Discount Program
• Employee Assistance & Work Life Program
• Outstanding training opportunities

DHL is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. The EEO is the Law poster is available here: https://www.eeoc.gov/employers/eeo-law-poster

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.