Experienced Data Scientist and Machine Learning Expert – Retail Industry Transformation through Advanced Statistical Modeling and Algorithm Development

Introduction to blithequark At blithequark, we are pioneering a revolution in the retail industry by harnessing the power of advanced statistical modeling, machine learning, and data science. Our mission is to transform retail operations by automating manual processes, enhancing decision-making, and driving business growth through data-driven insights. We are seeking an exceptional Data Scientist and Machine Learning Expert to join our team and play a pivotal role in shaping the future of retail. Job Overview As a Data Scientist and Machine Learning Expert at blithequark, you will lead the development and implementation of advanced forecasting algorithms, statistical models, and machine learning solutions to solve complex business problems in retail. Your expertise in data science methodologies, mathematical principles, and statistical techniques will enable us to make informed decisions, drive innovation, and stay ahead of the competition. You will work closely with our global AI team, scientists, engineers, and business partners to identify new opportunities, develop scalable solutions, and deploy them in a production environment. Key Responsibilities Develop and implement advanced forecasting algorithms, statistical models, and machine learning solutions to drive business growth and solve complex problems in retail Collect, organize, analyze, interpret, and summarize large datasets to generate key insights and inform business decisions Perform data exploration tasks, extract insights, and create storyboards from data analysis to present to stakeholders Build training workflows for machine learning algorithms on tens of millions of data points and create algorithmic solutions, including data ingestion, feature engineering, model development, validation, and deployment Lead and develop large-scale implementations of machine learning models and algorithmic solutions using rich retail data sources Review model performance, identify areas for improvement, and collaborate with the engineering team to address any issues in the production pipeline Utilize expertise in machine learning, probability theory, statistics, optimization theory, deep learning, data pipeline engineering, distributed systems, database architecture, linear programming, and data mining skills, along with programming languages such as SQL, R, Python, Spark, C, JavaScript, Scala, Hadoop, Hive, HTML, Matlab, Java, and Command Shell Requirements To be successful in this role, you must have: A Master's degree in Mathematics, Statistics, or a closely related quantitative field, and at least 7 years of experience as a data or machine learning scientist At least 2 years of experience working with large datasets, solving business problems, and developing data science solutions, including problem statement, feature engineering, model development, testing, and deployment to a production environment Experience with Hive or Hadoop, machine learning, text mining, and Spark Strong programming skills in languages such as Python, SQL, R, SAS, and data manipulation Excellent communication and collaboration skills, with the ability to present findings and reports to stakeholders Alternative Qualifications In lieu of the above requirements, we will consider candidates with: A Ph.D. degree in Mathematics, Statistics, or a closely related quantitative field, and at least 4 years of experience as a data or machine learning scientist At least 2 years of experience working with large datasets, solving business problems, and developing data science solutions, including problem statement, feature engineering, model development, testing, and deployment to a production environment Experience with Hive or Hadoop, machine learning, text mining, and Spark Strong programming skills in languages such as Python, SQL, R, SAS, and data manipulation Excellent communication and collaboration skills, with the ability to present findings and reports to stakeholders Career Growth and Learning Opportunities At blithequark, we are committed to the growth and development of our employees. As a Data Scientist and Machine Learning Expert, you will have access to: Ongoing training and professional development opportunities to enhance your skills and knowledge in data science and machine learning Collaboration with a global team of experts in AI, machine learning, and data science Opportunities to work on high-impact projects that drive business growth and innovation A dynamic and supportive work environment that encourages creativity, innovation, and experimentation Work Environment and Company Culture At blithequark, we pride ourselves on our collaborative and dynamic work environment. Our company culture is built on the values of innovation, creativity, and teamwork. We offer: A flexible and remote work arrangement, with the option to telecommute from any location in the U.S. A comprehensive benefits package, including health insurance, retirement savings, and paid time off A competitive salary and bonus structure, with opportunities for growth and advancement A supportive and inclusive work environment that values diversity, equity, and inclusion Compensation and Benefits We offer a comprehensive compensation and benefits package, including: A competitive salary and bonus structure A comprehensive benefits package, including health insurance, retirement savings, and paid time off Opportunities for growth and advancement, with a clear path for career development A dynamic and supportive work environment that encourages creativity, innovation, and experimentation Conclusion If you are a motivated and experienced Data Scientist and Machine Learning Expert looking to make a real impact in the retail industry, we encourage you to apply for this exciting opportunity at blithequark. With your expertise and our commitment to innovation and growth, we can transform the future of retail together. Apply now and join our team of experts in shaping the future of retail! Apply for this job