Description:
Role: Data Scientist - AI & Data
Location: San Francisco, CA
Responsibilities: -
Data Collection & Preparation:
• Gather, clean, and preprocess large datasets from various sources
• Perform exploratory data analysis (EDA) to understand the structure and quality of the data
• Apply data wrangling techniques to handle missing, inconsistent, or incomplete data
Statistical Analysis & Modeling:
• Use statistical techniques to identify patterns, correlations, and trends in data
• Develop predictive and prescriptive models using machine learning algorithms
• Build, test, and optimize models (e.g., regression, decision trees, random forests, SVM, deep learning, etc.
• Perform hypothesis testing and A/B testing to validate assumptions and recommendations
Machine Learning & AI Implementation:
• Implement machine learning models and algorithms for various business
• Leverage deep learning techniques and neural networks when necessary
• Monitor the performance of deployed models, providing regular updates
Data Visualization & Reporting:
• Create interactive and insightful visualizations using tools such as Tableau, Power BI, or libraries like Matplotlib and Seaborn (for Python).
• Present complex technical findings to non-technical stakeholders
• Prepare detailed reports and dashboards that track key performance indicators (KPIs) and other business metrics
Collaboration & Communication:
• Work closely with cross-functional teams, including business analysts, product managers, and engineers, to define project goals and requirements
• Communicate findings, methodologies, and insights effectively to both technical and business audiences
• Provide actionable recommendations to help drive data-informed decision-making
Continuous Improvement:
• Stay up-to-date with the latest research, tools, and techniques in data science and machine learning.
• Experiment with and implement cutting-edge machine learning algorithms and techniques.
• Contributes to the refinement and optimization of existing data models and processes.
Data Governance & Ethics:
• Ensure data integrity and privacy by following best practices in data handling and processing.
• Work in compliance with data security standards and ethical guidelines.
Requirements:
Skills and Qualifications:
Educational Background:
Bachelor's or Master's degree in Data Science, Computer Science, Mathematics, Statistics, or a related field. PhD is a plus.
Technical Skills:
• Strong proficiency in programming languages such as Python, R, or Java.
• Solid knowledge of statistical analysis and machine learning techniques.
• Hands-on experience with data manipulation and analysis using libraries like Pandas, NumPy, Scikit-learn, etc.
• Familiarity with big data technologies such as Hadoop, Spark, or similar.
• Experience with databases (SQL, NoSQL) and data extraction techniques.
• Familiarity with cloud platforms such as AWS, GCP, or Azure is a plus.
Analytical Skills:
• Excellent problem-solving abilities and critical thinking skills.
• Strong understanding of statistical methods, hypothesis testing, and data modeling
Soft Skills:
• Strong written and verbal communication skills.
• Ability to explain complex technical concepts to non-technical audiences.
• Detail-oriented with a strong focus on quality and accuracy.
Experience:
• Proven experience (2-5 years) in a data scientist role or similar.
• Experience in implementing machine learning models in a production environment is preferred.
• Experience with deep learning frameworks like TensorFlow, Keras, or PyTorch.
• Knowledge of NLP (Natural Language Processing) and computer vision techniques.
• Experience working with large-scale datasets in a cloud computing environment.
Work Environment:
• Collaborative and fast-paced work environment.
• Opportunity to work with state-of-the-art technologies.
• Supportive and dynamic team culture
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