AI Data Analysis Specialist

We are a dynamic and innovative company looking for an experienced AI Data Analysis Specialist to join our team. This role involves working with social networks, data enrichment tools, and AI-driven analytics to extract and analyze data for business intelligence. If you have a strong background in data analysis, AI tools, and LinkedIn API, we’d love to hear from you!

Responsibilities
– Collect, clean, and analyze structured and unstructured data from various sources.
– Develop and implement AI-driven models to extract insights and automate data processing.
– Create predictive analytics models to support decision-making processes.
– Build data visualization dashboards using tools like Power BI, Tableau, or similar.
– Optimize data pipelines for efficient storage, processing, and retrieval.
– Identify trends and patterns in large datasets to provide actionable business insights.
– Ensure data accuracy, integrity, and compliance with best practices.
– Collaborate with cross-functional teams, including marketing, finance, and product development, to support business strategies.

Requirements
– Proven experience in AI-driven data analysis and machine learning.
– Strong programming skills in Python, R, or SQL for data manipulation.
– Experience with data visualization tools (Power BI, Tableau, Google Data Studio).
– Knowledge of statistical analysis and predictive modeling techniques.
– Familiarity with cloud-based data platforms (AWS, GCP, Azure, or similar).
– Understanding of big data frameworks (Hadoop, Spark, or similar) is a plus.
– Strong problem-solving skills and attention to detail.
– Ability to work independently in a remote environment.

Nice-to-Have Skills
– Experience with automation tools for data processing.
– Knowledge of natural language processing (NLP) and AI-driven text analytics.
– Understanding of ETL pipelines and data warehousing.

Mandatory Skills
– Business Intelligence (BI)
– Data Analysis
– Data Scraping
– Data Visualization

Mandatory Languages
– English

Working Day
– Full Time Job

Working Conditions
– Monday to Friday
– Work Location: Remote