Tech-Nique Partners
Associate Director – Data Science & Analytics – Digital Americas
Tech-Nique Partners, New York, New York, us, 10261
Associate Director – Data Science & Analytics – Digital Americas
Base pay range
$160,000.00/yr - $180,000.00/yr
OVERVIEW The Associate Director, Data Science & Analytics will champion the consumer experience across all online channels through data‑driven strategies. This leadership position requires a deep understanding of the role that Data Science can play in retail and e‑commerce, applying advanced analytic data modeling and machine learning to all areas of the digital business to drive KPI optimization.
RESPONSIBILITIES
Lead the creation and implementation of best practices for statistical modeling, machine learning, and advanced analytics to support the Digital Americas business.
Oversee the design, development, and deployment of predictive and AI/ML models (e.g., churn prediction, price elasticity, LTV forecasting) that drive measurable business impact.
Provide hands‑on technical leadership in data science, machine learning, and data engineering; contribute to model design, algorithm development, and scalable MLOps practices.
Collaborate with Global teams to assess and enhance overall data architecture, ensuring alignment with strategic goals.
Champion the prioritization of Americas requests in Globally owned systems, from ticket/request development through proper implementation, QA and rollout.
Lead the integration of Americas third‑party tools with DWH, Liftlab and other Analytics team‑led systems.
QUALIFICATIONS
8–12 years of experience in eCommerce and Digital Marketing Data Science & Analytics, with a proven record of driving measurable business impact.
Strong technical foundation in SQL, Python, and/or R (experience with SAS a plus); advanced proficiency in statistical modeling, machine learning, and experimental design.
Hands‑on expertise with cloud platforms (AWS, GCP, Azure), big data tools (Spark, Databricks, Snowflake), ML frameworks (scikit‑learn, TensorFlow, PyTorch), and data visualization tools (Tableau, Power BI, Looker).
Skilled in web analytics platforms (Google Analytics, Omniture) and translating digital KPIs into actionable business insights.
Familiarity with MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and version control (Git).
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OVERVIEW The Associate Director, Data Science & Analytics will champion the consumer experience across all online channels through data‑driven strategies. This leadership position requires a deep understanding of the role that Data Science can play in retail and e‑commerce, applying advanced analytic data modeling and machine learning to all areas of the digital business to drive KPI optimization.
RESPONSIBILITIES
Lead the creation and implementation of best practices for statistical modeling, machine learning, and advanced analytics to support the Digital Americas business.
Oversee the design, development, and deployment of predictive and AI/ML models (e.g., churn prediction, price elasticity, LTV forecasting) that drive measurable business impact.
Provide hands‑on technical leadership in data science, machine learning, and data engineering; contribute to model design, algorithm development, and scalable MLOps practices.
Collaborate with Global teams to assess and enhance overall data architecture, ensuring alignment with strategic goals.
Champion the prioritization of Americas requests in Globally owned systems, from ticket/request development through proper implementation, QA and rollout.
Lead the integration of Americas third‑party tools with DWH, Liftlab and other Analytics team‑led systems.
QUALIFICATIONS
8–12 years of experience in eCommerce and Digital Marketing Data Science & Analytics, with a proven record of driving measurable business impact.
Strong technical foundation in SQL, Python, and/or R (experience with SAS a plus); advanced proficiency in statistical modeling, machine learning, and experimental design.
Hands‑on expertise with cloud platforms (AWS, GCP, Azure), big data tools (Spark, Databricks, Snowflake), ML frameworks (scikit‑learn, TensorFlow, PyTorch), and data visualization tools (Tableau, Power BI, Looker).
Skilled in web analytics platforms (Google Analytics, Omniture) and translating digital KPIs into actionable business insights.
Familiarity with MLOps, CI/CD pipelines, containerization (Docker, Kubernetes), and version control (Git).
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