About the Company
IBM is a global leader in technology and innovation, committed to creating solutions that address the world’s most pressing challenges. With a rich history spanning over a century, we empower businesses and individuals with cutting-edge software, hardware, and consulting services. Our teams are at the forefront of AI, cloud computing, quantum computing, and data analytics, driving progress across industries and fostering a culture of continuous learning and growth.
Job Description
We are seeking a highly motivated and skilled Pinterest Metadata Analyst with a strong focus on Machine Learning to join our innovative team in El Paso. In this role, you will be instrumental in analyzing, optimizing, and enhancing the metadata associated with Pinterest content, leveraging machine learning techniques to improve discoverability, relevance, and user experience. You will work closely with data scientists, product managers, and engineers to develop and implement data-driven strategies, ensuring the quality and integrity of our metadata infrastructure.
Key Responsibilities
- Analyze large datasets of Pinterest metadata to identify patterns, anomalies, and opportunities for improvement using SQL, Python, and statistical methods.
- Develop and apply machine learning models to automate metadata classification, tagging, and enrichment processes.
- Collaborate with data science and engineering teams to integrate ML-driven metadata solutions into production systems.
- Monitor the performance of metadata quality and ML models, performing regular audits and adjustments to ensure accuracy and effectiveness.
- Contribute to the design and implementation of A/B tests to evaluate the impact of metadata changes on key performance indicators.
- Stay abreast of the latest trends in machine learning, data science, and social media platforms, particularly Pinterest's evolving ecosystem.
- Prepare comprehensive reports and visualizations of metadata insights and model performance for various stakeholders.
- Provide expert recommendations on best practices for metadata management and optimization.
Required Skills
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
- 3+ years of experience in data analysis, business intelligence, or a related role with a focus on large datasets.
- Proficiency in SQL for data extraction and manipulation.
- Strong programming skills in Python (or R) with experience in data analysis libraries (e.g., Pandas, NumPy) and machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
- Experience with machine learning concepts and techniques, including classification, clustering, regression, and natural language processing.
- Familiarity with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
- Excellent analytical, problem-solving, and communication skills.
- Ability to work effectively in a collaborative team environment.
Preferred Qualifications
- Master's degree in a relevant field.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Familiarity with Pinterest's platform, API, or similar large-scale social media data.
- Experience with big data technologies (e.g., Spark, Hadoop).
- Proven track record of deploying machine learning models into production.
- Understanding of metadata standards and best practices.
Perks & Benefits
- Competitive salary and performance-based bonuses.
- Comprehensive health, dental, and vision insurance.
- 401(k) matching and retirement planning assistance.
- Paid time off, including vacation, sick leave, and holidays.
- Opportunities for professional development and continuous learning.
- Employee assistance programs and wellness initiatives.
- Dynamic and inclusive work environment.
How to Apply
If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:
- An up-to-date Resume or CV
- A brief cover letter summarizing your experience and motivation
Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.
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