The Senior Power BI & Data Analyst transforms complex commercial, operational and financial data into actionable insights that support strategic decisions, revenue growth, profitability and operational efficiency.
Responsibilities
Design and maintain enterprise Power BI dashboards, reports and semantic models.
Build advanced DAX measures, Power Query transformations and dimensional models.
Integrate ERP, CRM, finance and supply chain data; implement row-level security and refresh monitoring.
Senior Data Scientist responsible for designing and analyzing experiments, building models, and deriving insights to drive business metrics for a leading ecommerce platform.
Compensation
$80k–$120K USD
Responsibilities
Design, run, and analyze A/B tests measuring impact on key business metrics
Apply statistical methods and machine learning to solve business and product problems
Develop a deep understanding of search, ranking, and personalization algorithms
Analyze large-scale behavioral data to generate insights and recommendations
Build analyses, models, and tools that help teams make better decisions
We are seeking a highly skilled Data Scientist with proven expertise in Graph Neural Networks (GNNs) and Graph Machine Learning to lead the design, development, and implementation of graph-based AI models as part of a strategic Proof of Concept (POC).
Responsibilities
Design, build, and optimize Graph Neural Network (GNN) models for complex business problems.
Develop graph-based solutions for Link Prediction, Node Classification, Recommendation Systems, Network Analysis, Knowledge Graph Analytics, Fraud Detection, and Entity Resolution.
Build scalable graph data pipelines and feature engineering workflows.
Conduct model evaluation, experimentation, and performance optimization.
Collaborate with domain experts, architects, and engineering teams to deliver production-ready solutions.
An early-career Data Scientist role focused on working with structured and unstructured datasets to discover patterns, develop predictive models, and generate data-driven insights.
Locations (2)
United States
Canada
Responsibilities
Collect, clean, process, and analyze large datasets from multiple sources to identify patterns, trends, and meaningful insights.
Perform exploratory data analysis (EDA) to understand data distributions, relationships, and potential business opportunities.
Develop, train, test, and evaluate machine learning models to solve analytical and predictive problems.
Apply statistical techniques and mathematical methods to interpret data and support evidence-based decisions.
Write efficient code using Python and relevant data science libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib.
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