Senior Data Scientist

Senior Data Scientist

221 River Street, Hoboken, NJ 07030

Develop and implement advanced data science and artificial intelligence solutions to support business decision-making, including building, analyzing, and interpreting statistical, machine learning, and predictive models for large-scale datasets. Design and apply analytical approaches to evaluate business performance and identify key drivers of outcomes, including the impact of marketing and business initiatives. Build, analyze, and interpret large-scale analytical models, including Marketing Mix Models (MMM), to quantify the effectiveness of marketing investments, evaluate campaign performance, and identify optimization opportunities across channels and campaigns.

Perform advanced statistical analysis, including regression modeling, time-series analysis, and machine learning techniques, 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. Ensure model accuracy and robustness through validation, testing, and performance evaluation. Apply artificial intelligence and machine learning techniques to process large volumes of structured data and support scalable analytical solutions.

Write and optimize SQL queries and perform programming in Python to extract, transform, and analyze large datasets. Conduct exploratory data analysis, data validation, data cleaning, and feature engineering to prepare data for modeling. Work with large-scale data environments and cloud-based platforms to process and analyze data efficiently. Collaborate with cross-functional teams to understand business requirements, translate them into analytical frameworks, and deliver data-driven insights and recommendations.

Communicate complex analytical findings to stakeholders, including senior leadership, and support strategic decision-making by translating data insights into business actions. Research and apply industry best practices and emerging techniques in data science, machine learning, and artificial intelligence to continuously improve analytical methodologies and business outcomes.

• Master's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), Applied Data Science, or related field and 1 year of experience in an analytics related field; OR Bachelor's degree or equivalent in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, Engineering (any), Applied Data Science, or related field and 3 years of experience in an analytics related field.

• Experience with statistical modeling and predictive analytics using regression techniques for analyzing large-scale business and marketing datasets.
• Experience with Python including Pandas, Num Py, and Scikit-learn libraries for data processing, modeling, and analysis.
• Experience with SQL and relational database querying for data extraction, transformation, and aggregation from large datasets.
• Experience with exploratory data analysis (EDA), data cleaning, and feature engineering to prepare data for statistical modeling and analysis.
• Experience with machine learning model development, validation, and performance evaluation using standard statistical and computational techniques.
• Experience with time-series analysis and forecasting techniques for evaluating trends and patterns in business data.
• Experience with causal inference and quasi-experimental methodologies including Difference-in-Differences techniques for measuring business and marketing impact.
• Experience with marketing and business analytics, including measurement of performance metrics such as return on investment and channel contribution analysis.
• Experience with data integration and handling of 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 with the design and evaluation of controlled experiments and A/B testing methodologies for business applications.
• Experience with working with cloud-based data platforms for storage, processing, and analysis of large datasets.

$115,835/year to $216,000/year. Additional compensation includes annual or quarterly performance incentives.

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