Data Scientist
Role details
Job location
Tech stack
Job description
We are seeking a Data Scientist who thrives at the intersection of data transformation, analytics, and implementation. In this role, the Data Scientist will partner directly with clients to prepare, clean, and transform their data so it can seamlessly integrate with our aiCast platform. This Data Scientist will help customers unlock the value of their data-building pipelines, dashboards, and forecasts-and in many cases, own the end-to-end implementation from ingestion through delivery. This Data Scientist position is centered on data engineering, applied analytics, and client enablement. You'll play a key role in helping customers get from raw data to actionable insights. Responsibilities: Collaborate with client teams to understand their data sources, structures, and business requirements. Design and implement data transformation pipelines to prepare data for aiCast ingestion. Build reporting and dashboarding solutions to help clients interpret and act on their data. Develop forecasting and analytics workflows to extend client use cases beyond data prep. Support end-to-end solution delivery-covering extraction, transformation, validation, and deployment-when applicable. Troubleshoot data quality issues and provide recommendations for improved structures or processes. Partner with internal engineering and success teams to ensure smooth implementations and knowledge transfer., As a Data Visualization Scientist, you will leverage your expertise in scientific visualization and fluid dynamics simulation to enhance AI research. This role offers the flexibili…
- 14 days ago
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Requirements
At least 1-3 years of experience in a data role, preferably with enterprise clients Associate's or Bachelor's degree in a relevant field (e.g., Computer Science, Statistics, or Applied Mathematics) preferred Proficiency in Python, including libraries like NumPy and Pandas for data transformation. Working knowledge of SQL for querying and joining datasets (intermediate level). Experience building ETL/ELT pipelines or similar data processing workflows. Familiarity with data visualization, reporting, or dashboarding tools. Strong problem-solving skills with a focus on client outcomes and practical implementation. Ability to work with incomplete or messy data and structure it for usability in production systems. Excellent communication skills for translating technical work into business impact. Preferred Skills: Knowledge of data transformation (e.g. using python Pandas library) database management, data integration, or data visualization is a plus Experience with forecasting techniques or applied time-series analytics. Background in client-facing or consulting roles where you owned implementation delivery. Understanding of software engineering best practices (version control, testing, deployment).
Benefits & conditions
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