ABOUT FUSEMACHINES

Fusemachines is a leading AI strategy, talent, and education services provider. Founded by Sameer Maskey Ph.D., Adjunct Associate Professor at Columbia University, Fusemachines has a core mission of democratizing AI. With a presence in 4 countries (Nepal, United States, Canada, and Dominican Republic and more than 350 full-time employees). Fusemachines’ AI educational program has made world-class AI education available, accessible and affordable to students around the world. Fusemachines seeks to bring its global expertise in AI to transform companies around the world.

JOB DESCRIPTION:

We are seeking a talented and experienced Data Analyst with expertise in Power BI, and Azure public cloud provider to join our team. The Data Analyst will be responsible for gathering, interpreting, analyzing and visualizing large and complex datasets to provide insights and support data-driven decision-making within the organization.

REQUIREMENTS:

• Bachelor’s or master’s degree in a quantitative field such as statistics, mathematics, or computer science
• At least 5 years of experience in data analytics, with a focus on business intelligence and data visualization
• At least 3 years of experience using Power BI to design, build and maintain dashboards and reports
• Nice to have experience with Tableau
• 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 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.
  If you are a data-driven individual with strong leadership skills and experience with PowerBI and Tableau we encourage you to apply for this exciting opportunity.
  Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status
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RESPONSIBILITIES:

• 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 Tableau, Power BI, and Python libraries (e.g., Matplotlib, Seaborn).
• 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.