Data Scientist/Analyst
Apply NowCompany: Resource Informatics Group
Location: San Francisco, CA 94112
Description:
Position: Data Scientist/Analyst
Location: San Francisco, CA (Onsite)
Duration: Long Term Contract
Responsibilities:
Data Cleansing and Preparation:
Develop and implement robust data cleansing and preprocessing pipelines to ensure data quality and consistency.
Extract, transform, and load (ETL) data from various sources, including POS systems, inventory management systems, and customer databases.
Identify and resolve data anomalies, inconsistencies, and missing values.
Create and maintain comprehensive data documentation.
Retail Client Analysis:
Conduct in-depth analysis of sales, inventory, and customer data to identify trends, patterns, and opportunities.
Develop and implement predictive models for demand forecasting, inventory optimization, and customer segmentation.
Analyze the impact of marketing campaigns and promotional activities on sales and customer behavior.
Generate actionable insights and recommendations to optimize business performance.
Agentic Frameworks:
Research, evaluate, and implement Agentic frameworks to automate data analysis and decision-making processes.
Develop and deploy intelligent agents for tasks such as data extraction, anomaly detection, and report generation.
Integrate Agentic frameworks with existing data pipelines and analytical tools.
Explore and experiment with emerging AI technologies to enhance data-driven capabilities.
Collaboration and Communication:
Collaborate with cross-functional teams, including sales, marketing, and supply chain, to understand business requirements and deliver data-driven solutions.
Communicate complex data insights to stakeholders in a clear and concise manner.
Present data findings and recommendations through visualizations and reports.
About the Role:
We are seeking a highly motivated and experienced Data Scientist/Analyst with a strong background in the Retail Client industry to join our dynamic data team. In this role, you will be instrumental in transforming raw data into actionable insights, driving strategic decisions, and leveraging cutting-edge Agentic frameworks to automate and enhance data-driven processes. You will play a critical role in optimizing our supply chain, marketing strategies, and customer experience.
Requirements:
Bachelor's or master's degree in data science, Statistics, Computer Science, or a related field.
Strong proficiency in SQL and Python (Pandas, NumPy, Scikit-learn).
Experience with data visualization tools (e.g., Tableau, Power BI).
Solid understanding of statistical modeling and machine learning techniques.
Proven ability to clean, process, and analyze large datasets.
Experience with ETL processes and data warehousing.
Strong analytical and problem-solving skills.
Excellent communication and presentation skills.
Preferred Qualifications:
Experience with Agentic frameworks (e.g., Auto-GPT, LangChain, etc.).
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
Experience with time series analysis and forecasting.
Knowledge of supply chain management and inventory optimization.
Experience with customer segmentation and lifetime value analysis.
Knowledge of natural language processing (NLP) and text analysis.
Experience with LLMs.
Experience with Retail POS data.
Location: San Francisco, CA (Onsite)
Duration: Long Term Contract
Responsibilities:
Data Cleansing and Preparation:
Develop and implement robust data cleansing and preprocessing pipelines to ensure data quality and consistency.
Extract, transform, and load (ETL) data from various sources, including POS systems, inventory management systems, and customer databases.
Identify and resolve data anomalies, inconsistencies, and missing values.
Create and maintain comprehensive data documentation.
Retail Client Analysis:
Conduct in-depth analysis of sales, inventory, and customer data to identify trends, patterns, and opportunities.
Develop and implement predictive models for demand forecasting, inventory optimization, and customer segmentation.
Analyze the impact of marketing campaigns and promotional activities on sales and customer behavior.
Generate actionable insights and recommendations to optimize business performance.
Agentic Frameworks:
Research, evaluate, and implement Agentic frameworks to automate data analysis and decision-making processes.
Develop and deploy intelligent agents for tasks such as data extraction, anomaly detection, and report generation.
Integrate Agentic frameworks with existing data pipelines and analytical tools.
Explore and experiment with emerging AI technologies to enhance data-driven capabilities.
Collaboration and Communication:
Collaborate with cross-functional teams, including sales, marketing, and supply chain, to understand business requirements and deliver data-driven solutions.
Communicate complex data insights to stakeholders in a clear and concise manner.
Present data findings and recommendations through visualizations and reports.
About the Role:
We are seeking a highly motivated and experienced Data Scientist/Analyst with a strong background in the Retail Client industry to join our dynamic data team. In this role, you will be instrumental in transforming raw data into actionable insights, driving strategic decisions, and leveraging cutting-edge Agentic frameworks to automate and enhance data-driven processes. You will play a critical role in optimizing our supply chain, marketing strategies, and customer experience.
Requirements:
Bachelor's or master's degree in data science, Statistics, Computer Science, or a related field.
Strong proficiency in SQL and Python (Pandas, NumPy, Scikit-learn).
Experience with data visualization tools (e.g., Tableau, Power BI).
Solid understanding of statistical modeling and machine learning techniques.
Proven ability to clean, process, and analyze large datasets.
Experience with ETL processes and data warehousing.
Strong analytical and problem-solving skills.
Excellent communication and presentation skills.
Preferred Qualifications:
Experience with Agentic frameworks (e.g., Auto-GPT, LangChain, etc.).
Familiarity with cloud platforms (AWS, Azure, GCP) and their data services.
Experience with time series analysis and forecasting.
Knowledge of supply chain management and inventory optimization.
Experience with customer segmentation and lifetime value analysis.
Knowledge of natural language processing (NLP) and text analysis.
Experience with LLMs.
Experience with Retail POS data.