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 statistica l 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 Salary Range: $165,750 - $246,675 a year #LI-AD1