Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clientsâ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail, manufacturing, and government.
Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
Type: Remote, Full-time
Important: Immigration Sponsorship Policy
This position is not eligible for employment visa sponsorship or transfer sponsorship now or in the future.
- Direct Company Sponsorship: Such as H-1B, J-1, or TN visas
- Employer of Record: Listing Fusemachines as the immigration employer on any government documentation
- Written Documentation: Providing letters or other support for any work authorization (e.g., OPT, STEM OPT, CPT)
We are seeking a talented and experienced Data Analyst responsible for gathering, interpreting, analyzing, and visualizing large and complex datasets to provide insights and support data-driven decision-making (BI, visualization, and Advanced Analytics).
Qualification / Skill Set Requirement:
- Data Collection and modeling: Gathering data from various sources such as databases, spreadsheets, APIs, and other relevant sources to support business requirements
- Data Cleaning and Preprocessing: Reviewing and organizing data to ensure accuracy, consistency, and completeness. This may involve handling missing values, removing outliers, and transforming data into a suitable format for analysis
- Data Analysis: Applying statistical techniques and analytical methods to examine data and identify patterns, trends, relationships and insights that inform business decisions. This will involve using tools like SQL, Python or specialized data analysis software
- Data Visualization : Design, build and maintain visual representations of data through charts, graphs, and dashboards to communicate insights effectively to stakeholders. Data visualization tools like SnowSight, and Power BI
- Reporting: Summarizing and presenting findings from data analysis in a clear and concise manner. This includes creating reports, slide decks, or presentations to communicate insights and recommendations to non-technical stakeholders
- Data Governance, including Quality Assurance: Ensuring the accuracy, consistency, and integrity of data by performing quality checks and validation procedures. This involves identifying and resolving data discrepancies or errors
- Data Mining: Identifying patterns, trends, and correlations in large datasets to extract meaningful information and support business objectives. This may involve using techniques like clustering, classification, regression, or association analysis
- Statistical Analysis: Applying statistical methods and hypothesis testing to draw meaningful conclusions from data and make data-driven recommendations
- Identifying and implementing best practices for data visualization, reporting and analysis
- Collaborating with Teams: Working closely with cross-functional teams, such as business analysts, data engineers, and decision-makers, to understand their requirements, provide analytical support, identify key metrics and contribute to data-driven initiatives to solve business challenges
- Continuous Learning: Staying updated with industry trends, new analytical techniques, and tools to enhance data analysis capabilities and improve efficiency
- Bachelor's or master's degree in a quantitative field such as statistics, mathematics, or computer science
- At least 8 years of experience in data analytics, with a focus on business intelligence and data visualization
- 5+ years of real-world data engineering development experience in Snowflake
- Proficient in the application of DBT
- Proficient in Snowflake services such as SnowSight, Snowpipe, stages, stored procedures, views, materialized views, tasks and streams
- Strong SQL skills and experience working with complex data sets and Enterprise Data Warehouse
- Experience with data modeling and schema design
- Strong analytical and problem-solving skills with the ability to translate complex data into actionable insights
- Excellent communication and collaboration skills with the ability to work effectively with cross-functional teams, are essential to convey complex technical concepts and insights to non-technical stakeholders effectively
- Demonstrated leadership experience with the ability to mentor and develop junior analysts
- Experience with data governance, data quality, and data integrity efforts
- Attention to Detail: Being meticulous and paying attention to detail is critical in data analysis. Small errors or inaccuracies can lead to misleading results, so data analysts should have a keen eye for detail and double-check their work
- Strong project management skills with the ability to manage multiple projects and priorities simultaneously
- for data integration, storage, processing, and manipulation
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