About Appen

Appen is a leader in AI enablement for critical tasks such as model improvement, supervision, and evaluation. To do this we leverage our global crowd of over one million skilled contractors, speaking over 180 languages and dialects, representing 130 countries. In addition, we utilize the industry's most advanced AI-assisted data annotation platform to collect and label various types of data like images, text, speech, audio, and video.

Our data is crucial for building and continuously improving the world's most innovative artificial intelligence systems and Appen is already trusted by the world's largest technology companies. Now with the explosion of interest in generative AI, Appen is helping leaders in automotive, financial services, retail, healthcare, and governments the confidence to deploy world-class AI products.

At Appen, we are committed to creating an inclusive and diverse workplace. We are an equal opportunity employer that does not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

CrowdGen

CrowdGen is a leading global platform supporting companies in building and launching AI. As one of the largest AI data services companies, we enable global enterprises to develop and deploy large-scale AI models and applications. With a network of over 1 million Contributors in 185+ countries, CrowdGen connects highly skilled independent contractors with AI data projects that require diverse expertise in over 500 languages. Our projects range from quick-turn, high-volume tasks to long-term, complex deliverables.

Position Overview:

We are seeking a proactive and detail-oriented Business Data Analyst to take ownership of analyzing, monitoring, and optimizing our global contributor workforce, including productivity, performance, pay, and feasibility.

The ideal candidate will excel in processing, modelling, and analyzing complex data sets to derive actionable insights that drive strategic business decisions. This role requires a blend of technical expertise, analytical skills, and the ability to collaborate with various departments, including delivery, operations, sales, and marketing, to provide a competitive advantage through data-driven insights.

You will play a key role in assessing contributor performance trends, optimizing financial and operational impact of pay rate changes, identifying workforce insights across diverse geographies and skill sets, and supporting initiatives that drive contributor engagement, operational efficiency, and long-term sustainability. This role is ideal for someone looking to move from a consulting, workforce analytics, or operations strategy background into a dynamic, high-impact position in a fast-paced tech environment.

Reporting to the Director of Crowd Management, this role will involve:

Technical Process Development:

Design and build technical processes to address business issues and optimize operations.

Collaboration:

Work closely with cross-functional teams to understand their data needs and provide analytical support.
Communicate results and business impacts of data insights to stakeholders within and outside the company.

Reporting:

Generate and present regular and ad-hoc reports, summarizing key findings and recommendations.

Project Management:

Organize and drive successful completion of data insight initiatives through effective management and collaboration

Experience:

At least 3 years of experience in a data analysis role, monitoring, managing, and drawing insights from data.
Proficiency with Excel, Word, and PowerPoint.

Technical Skills:

Proficiency in SQL, Python, R, or other programming languages used for data analysis.
Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
Understanding of modern data platforms like Snowflake, Databricks, GBQ, etc.
Familiarity with business platforms like Salesforce, Workday, etc.

Analytical Skills:

Strong problem-solving, quantitative, and analytical abilities.
Knowledge of statistical modelling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.
Experience with predictive analytics, data mining, and mapping.

Communication:

Excellent written and verbal communication skills, with the ability to present complex information clearly and concisely.

Attention to Detail:

High level of accuracy and attention to detail in work outputs.

Project Management:

Ability to plan and manage multiple processes, projects, and teams simultaneously.
Strong collaboration and delegation skills.