Senior Data Scientist
About The Position
The Senior Data Scientist develops and implements advanced data science and artificial intelligence solutions to support business decision-making. The role builds, analyzes, and interprets statistical, machine-learning, and predictive models for large-scale datasets, and designs analytical approaches to evaluate business performance and identify drivers of outcomes, including the impact of marketing and business initiatives. The position develops and interprets large-scale analytical models, including Marketing Mix Models (MMM), to measure marketing-investment effectiveness, assess campaign performance, and identify optimization opportunities across channels and campaigns. It applies statistical analysis, regression, time-series analysis, machine learning, causal inference, and experimental methods to generate actionable business insights. The role also uses SQL and Python to extract, transform, and analyze data; prepares data through exploration, validation, cleaning, and feature engineering; and works with large-scale data environments and cloud platforms. The Senior Data Scientist collaborates with cross-functional teams to translate business requirements into analytical frameworks and recommendations, communicates findings to stakeholders including senior leadership, and researches emerging techniques and industry practices to improve analytical methodologies and business outcomes. The position is located at 221 River Street, Hoboken, NJ 07030.
Requirements
- A master’s degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), Applied Data Science, or a related field, plus 1 year of experience in an analytics-related field; or a bachelor’s degree or equivalent in one of those fields, plus 3 years of experience in an analytics-related field.
- Experience with statistical modeling and predictive analytics using regression techniques to analyze large-scale business and marketing datasets.
- Experience with Python, including Pandas, NumPy, and Scikit-learn, for data processing, modeling, and analysis.
- Experience with SQL and relational database querying to extract, transform, and aggregate large datasets.
- Experience with exploratory data analysis, data cleaning, and feature engineering to prepare data for statistical modeling and analysis.
- Experience developing, validating, and evaluating machine-learning models using standard statistical and computational techniques.
- Experience with time-series analysis and forecasting for evaluating business-data trends and patterns.
- Experience with causal inference and quasi-experimental methods, including Difference-in-Differences, to measure business and marketing impact.
- Experience with marketing and business analytics, including measuring return on investment and analyzing channel contribution.
- Experience integrating and handling large datasets from multiple sources, including structured and semi-structured data environments.
- Experience with data visualization and reporting using analytical tools to communicate insights and support decision-making.
- Experience designing and evaluating controlled experiments and A/B testing for business applications.
- Experience working with cloud-based data platforms for storage, processing, and analysis of large datasets.
- The employer will accept any amount of experience with the required skills.
Responsibilities
- Develop and implement data science and artificial intelligence solutions that support business decision-making.
- Build, analyze, and interpret statistical, machine-learning, and predictive models for large-scale datasets.
- Design analytical approaches to evaluate business performance and identify key drivers of outcomes, including the effects of marketing and business initiatives.
- Develop and analyze Marketing Mix Models (MMM) to quantify marketing-investment effectiveness, evaluate campaign performance, and identify optimization opportunities across channels and campaigns.
- Perform regression modeling, time-series analysis, and other advanced statistical and machine-learning analyses to quantify trends, relationships, and business impact.
- Develop, train, validate, and refine predictive models and algorithms, and apply them to new datasets to generate actionable insights.
- Validate, test, and evaluate model performance to ensure accuracy and robustness.
- Apply AI and machine-learning techniques to process large volumes of structured data and support scalable analytical solutions.
- Write and optimize SQL queries and use Python to extract, transform, and analyze large datasets.
- Conduct exploratory data analysis, data validation, data cleaning, and feature engineering to prepare data for modeling.
- Use large-scale data environments and cloud-based platforms to process and analyze data efficiently.
- Collaborate with cross-functional teams to understand business requirements, develop analytical frameworks, and deliver data-driven insights and recommendations.
- Communicate complex analytical findings to stakeholders, including senior leadership, and translate insights into business actions to support strategic decisions.
- Research and apply industry best practices and emerging data science, machine-learning, and artificial-intelligence techniques to improve analytical methodologies and business outcomes.
Benefits
- Medical, vision, and dental coverage.
- 401(k).
- Stock purchase plan.
- Company-paid life insurance.
- Paid time off, including sick leave.
- Parental leave.
- Family care leave.
- Bereavement leave.
- Jury duty and voting leave.
- Short-term and long-term disability.
- Education assistance, including 100% company-paid college degrees.
- Company discounts.
- Military service pay.
- Adoption expense reimbursement.
- Performance-based incentive awards and annual or quarterly performance incentives.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
