Data Scientist

Work Authorization

Candidates must currently reside in the Pittsburgh area and be available for a hybrid schedule. This opportunity is for direct hire only and is not available for C2C, third-party submissions, or visa sponsorship

Data Scientist

We are seeking a versatile Data Scientist to join our team in Pittsburgh, PA. This is a direct hire position offering a hybrid work schedule for candidates who currently reside in the Pittsburgh area. This role is not open to C2C, visa sponsorship, or third parties.

Role Overview

In this role, you will design, build, and optimize data pipelines while also delivering advanced analytics, predictive modeling, and business insights. You will work across modern cloud platforms and leverage Microsoft Fabric to unify data engineering, analytics, and business intelligence efforts. Microsoft Fabric’s integrated ecosystem supports OneLake, Lakehouse, Data Warehouse, Data Factory, Dataflows Gen2, Eventstream, Spark notebooks, and Power BI, making it well suited for this type of end-to-end analytics work.

Key Responsibilities

• Design, develop, and maintain interactive dashboards and analytical solutions in Power BI, including Direct Lake semantic models, Copilot-enabled experiences, paginated reports, and executive scorecards. Power BI Copilot provides chat-based analysis and support for tasks such as DAX generation and on-the-fly analysis.

• Build KPI-driven dashboards for pricing analytics, POS sales trends, inventory optimization, supply chain performance, customer purchasing behavior, and branch/DC operational analytics.

• Enable self-service analytics through governed semantic models, curated datasets, and reusable reporting assets. Direct Lake semantic models are optimized for large data volumes in Fabric.

• Develop predictive and prescriptive models for dynamic pricing, sales forecasting, demand planning, customer segmentation, lost sales analysis, and inventory replenishment.

• Apply machine learning and AI techniques using Python, Spark notebooks, Fabric Data Science workloads, and Azure AI / OpenAI capabilities. Fabric supports Azure OpenAI and related AI services through integrated tooling.

• Support AI-driven initiatives such as Copilot-enabled analytics, conversational BI, sentiment analysis, speech-to-text analytics, and agentic AI use cases.

• Work extensively within the Microsoft Fabric ecosystem, including OneLake, Lakehouse, Data Warehouse, Data Factory, Dataflows Gen2, Eventstream / Real-Time Intelligence, Spark notebooks, semantic models, and Power BI.

• Support ingestion and transformation of enterprise data from Oracle, SQL Server, APIs, SaaS platforms, XML/JSON log files, and event streaming platforms.

• Partner with Pricing, Sales, Supply Chain, Operations, and IT teams to translate business needs into technical analytics solutions and present findings to leadership.

• Contribute to enterprise data modernization and cloud transformation initiatives.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Information Systems, Engineering, Statistics, Mathematics, or a related field.

• 3–5 years of experience in Data Analytics, Business Intelligence, Data Science, or a related analytics role.

• Strong experience with Power BI, SQL, data modeling, and dashboard development.

• Experience with Microsoft Azure and/or Microsoft Fabric.

• Proficiency in Python for analytics and data manipulation.

• Experience working with large enterprise datasets.

Preferred Qualifications

• Experience with Microsoft Fabric services such as Lakehouse, Spark, Data Factory, Real-Time Analytics, and semantic models.

• Familiarity with machine learning frameworks and core AI/ML concepts.

• Knowledge of pricing analytics, supply chain analytics, inventory optimization, and wholesale/distribution analytics.

• Experience with REST APIs, event streaming, Kafka/Event Hub, and XML/JSON data processing.

• Familiarity with cloud data warehouse modernization initiatives.

• Microsoft certifications in Azure, Power BI, Fabric, or Data Engineering are a plus.

Technical Skills