Jobs at Prescience Decision Solutions

Develop machine-learning and analytical solutions for loyalty programs, including segmentation, propensity, recommendation, uplift, optimization, experimentation, and causal-impact measurement. Translate business questions into actionable recommendations, establish success metrics, partner cross-functionally on production-ready solutions, and support loyalty data platforms and products. Ensure data quality, reproducibility, governance, and responsible customer-data use while communicating findings to technical and executive audiences.

Develop machine-learning and advanced analytics solutions for loyalty programs, including segmentation, propensity, recommendation, uplift, optimization, experimentation, and causal measurement. Partner with product, marketing, engineering, and analytics teams to improve acquisition, engagement, retention, and customer lifetime value. Establish success metrics, ensure data quality and model governance, contribute to data products, and communicate actionable insights to technical and senior business stakeholders.

Owns Finance data architecture across transactional and analytical platforms. Designs data models, pipelines, integration patterns, governance standards, reconciliation controls, and data quality frameworks using MySQL, PostgreSQL, Hive, and Spark. Provides technical leadership, architecture reviews, mentorship, and long-term platform strategy while partnering with Finance, Engineering, Analytics, and Operations stakeholders.

Leads Azure Databricks platform solutioning, architecture, implementation, security, governance, networking, Infrastructure-as-Code, CI/CD, and data pipeline design. Establishes Unity Catalog, scalable ETL/ELT workflows, and lakehouse modernization strategies. Provides technical leadership through mentoring, hiring, delivery oversight, client pitches, RFP responses, and practice development across data engineering, AI, machine learning, and AI operations.

Design and implement scalable Lakehouse architectures and ETL/ELT pipelines using Databricks, PySpark, SparkSQL, Delta Lake, and DBT. Optimize SQL and data performance, model data, integrate ERP systems, and support governance, lineage, security, CI/CD, and automated deployments.

Lead analytics delivery across data engineering, reporting, and business intelligence. Develop SQL-based insights in Snowflake using dbt, maintain dashboards, monitor data quality, and translate complex questions into actionable conclusions. Own client deliverables, establish quality standards, manage priorities, and serve as an escalation point. Lead and mentor 3–4 analysts while partnering with stakeholders, Engineering, Product, and Operations to communicate findings and improve reporting infrastructure.

Analyze product data using advanced SQL, Python, Tableau, and experimentation methods. Interpret A/B test results, conduct power analysis, define and evaluate metrics, build complex self-service dashboards and data pipelines, investigate root causes, solve business problems, and communicate insights clearly in English.