Data Scientist

Data Scientist/AnalystHigh level overview of this role is a Data Scientist/Analyst who will sit with Walmart Business and analyze the data from Walmart IoT Energy Devices (refrigeration, lighting, HVAC, etc).We are looking for an SME who can come in and connect the dots between our data and our devices to help them run as efficiently as possibleMust Have skills:Create SQL queries and be able to analyze highly complex data setsData Mining expertiseHave experience working in the energy industry (HVAC, Lighting, refrigeration, etc.)Some of these companies: Emerson, Danfoss, Carel etcTheir Tech stack is Java, Spark, Python; while they don't need to be able to program using them, they should understand how they wrap up into the device applicationsNice to Have:BS or MS in EEJob Description:We are seeking a highly skilled and motivated Data Analyst/Data Scientist to join our team. In this role, you will be responsible for interpreting and analyzing data flowing through our energy devices (Lighting, HVAC, Refrigeration, etc) to identify opportunities for improving efficiency, reducing costs, and maximizing the performance of our clients' power systems.Responsibilities:Data Interpretation: Analyze large volumes of data from power meters to identify opportunities for improving efficiency, reducing costs, and maximizing the performance of our clients' power systems.Statistical Analysis: Apply statistical methods and techniques to extract meaningful insights from IoT Device data and identify patterns or trends.Data Cleaning and Preparation: Preprocess and clean raw data to ensure accuracy and consistency, removing outliers and irrelevant information.Data Visualization: Create clear and visually appealing data visualizations, including charts, graphs, and reports, to present findings and insights to both technical and non-technical stakeholders (Power BI)Collaborative Problem Solving: Work closely with cross-functional teams, including engineers, operations personnel, and clients, to understand their needs and provide data-driven solutions.Performance Monitoring: Monitor power meter data in real-time to identify any sudden changes or deviations from normal patterns and promptly investigate and resolve any issues.Reporting and Documentation: Prepare comprehensive reports summarizing findings, recommendations, and insights, and document data analysis methodologies and processes for future reference.Continuous Improvement: Stay up to date with the latest advancements in data analysis techniques, tools, and technologies, and suggest improvements to enhance data analysis capabilities.Qualifications:Education: Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field.A strong academic background in mathematics and statistics is highly desirable.Experience: Minimum of 5 years of experience as a Data Analyst, Data Scientist, or a similar role, preferably working with large datasets and conducting statistical analysis.Skills: Proficient in data analysis techniques, including data cleaning, preprocessing, statistical analysis, and predictive modeling. Technologies used include SQL queries, Spark, Java, Python and AZUREDomain Knowledge: Familiarity with power systems, energy management, or the utility industry is critical, along with an understanding of power meter data and relevant metrics.Problem-Solving Abilities: Strong analytical thinking and problem-solving skills, with the ability to translate complex data into actionable insights and recommendations.Communication Skills: Excellent verbal and written communication skills to effectively convey complex data analysis concepts to both technical and non-technical stakeholders.Team Player: Ability to collaborate effectively with cross-functional teams, share knowledge, and work towards common goals.Attention to Detail: Meticulous attention to detail and accuracy in data analysis, with the ability to identify and correct errors or inconsistencies. Adaptability: Comfortable working in a fast-paced environment and handling multiple projects simultaneously while meeting deadlines.