
Lina Jariga
Accounting / Finance
About Lina Jariga:
Hello! I'm Lina Jariga, a Data Analyst from San Jose with a robust background in financial and marketing analytics. With seven years of experience, I adeptly turn complex data into actionable insights using SQL, Python, and Tableau. Recently, I expanded my expertise with a Machine Learning course from Stanford, aiming to apply these cutting-edge skills in dynamic business environments. I'm passionate about leveraging data to drive strategic decisions and innovation. Let’s connect if you’re looking for impactful data-driven solutions
Experience
I am a seasoned Data Analyst with over seven years of experience in data analytics and financial analysis, skilled in using SQL, Python, and Tableau to deliver actionable business insights. My career began in Lithuania, where I worked in finance and auditing, before moving to Dublin to specialize in tax compliance and investment analysis at Meridian Global Services and Zurich Insurance Group. Since relocating to San Jose, I have freelanced, applying my analytical skills to help businesses optimize operations and enhance decision-making. My recent completion of Stanford's Machine Learning for Business with Python course has further honed my capabilities, preparing me to tackle sophisticated analytics challenges in dynamic market environments.
Education
I am currently enrolled in Stanford's 'BUS 48 Practical Analytics: Transforming Data into Decisions' course, where I am deepening my analytical skills under the guidance of Moe Lotfy. This 10-week course focuses on converting data into actionable insights, a crucial skill for data-driven decision making in business. The curriculum is divided into two main sections: the first covers analytics project scoping, data preparation, and visualization; the second delves into advanced analytical techniques and responsible AI, including A/B testing and machine learning. This training is enhancing my ability to interpret data effectively and use it to inform strategic business decisions, making it highly relevant to my professional growth in data and marketing analytics.
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