Experienced Full Stack Data Entry Specialist – Retail Operations and Analytics

Are you a highly skilled and detail-oriented individual with a passion for data analysis and entry? Do you have a strong background in mathematics, statistics, or a related quantitative field? If so, we encourage you to apply for this exciting opportunity to join arenaflex as a Full Stack Data Entry Specialist – Retail Operations and Analytics.

About arenaflex

arenaflex is a leading company in the retail industry, dedicated to providing innovative solutions and services to our clients. We are committed to excellence and strive to create a work environment that is collaborative, inclusive, and supportive. Our team is passionate about using data-driven insights to drive business growth and improve customer experiences.

Job Summary

As a Full Stack Data Entry Specialist – Retail Operations and Analytics, you will be responsible for leading the improvement and alertness of mathematical and statistical ideas and techniques to create long-term forecasting algorithms that solve business problems in retail. You will transform how retail operations work by automating various tasks that currently require manual attention and decision-making through arithmetic and statistical models. You will collect, organize, analyze, interpret, and summarize large amounts of time-series data to generate key insights leading to new revolutionary applications.

Key Responsibilities

* Lead the improvement and alertness of mathematical and statistical ideas and techniques to create long-term forecasting algorithms that solve business problems in retail

• Transform how retail operations work by automating various tasks that currently require manual attention and decision-making through arithmetic and statistical models
• Collect, organize, analyze, interpret, and summarize large amounts of time-series data to generate key insights leading to new revolutionary applications
• Analyze complex and rich data, examine business problems, develop problem statements, outline metrics, and drive feasibility studies
• Perform data exploration tasks, extract insights, and create storyboards from data analysis
• Present clear and accurate root-cause analysis to stakeholders and leadership
• Build education workflows for system learning algorithms on tens of millions of data points and create algorithmic solutions including data science, feature engineering, model development, validation, and model deployment
• Lead and develop large-scale implementations of system learning models and algorithmic solutions using rich retail data sources
• Review model performance and identify upgrades to improve models
• Collaborate with global AI teams, scientists, engineers, and business partners to identify and lead new opportunities
• Utilize skills in system learning, risk theory, and statistics, optimization theory, deep learning, data pipeline engineering, distributed systems, database architecture, linear programming, and data mining, including SQL, R, Python, Spark, C, JavaScript, Scala, Hadoop, Hive, HTML, Matlab, Java, and Command Shell programming
• Advocate excellent software engineering practices and capable of prototyping individual components of data science solutions

Requirements

* At least a Master's degree in Mathematics, Statistics, or a closely related quantitative field, and at least seven (7) years of experience as an information or system learning scientist (any title) including undertaking advanced system learning activities (regression, clustering, and forecasting)

• Using the development and implementation of analytical and data science modeling solutions using techniques such as data mining, system learning, or text mining
• Using mathematical concepts, algorithms, and computational complexity
• Participating with colleagues to bring business value to the organization
• Presenting findings and reports to stakeholders
• Using Python, SQL, R, SAS, risk evaluation, and data manipulation
• Must include at least two (2) years working with large quantities of data and solving business problems
• Working on presenting data science solutions including problem statement, feature engineering, model development, assessment, and testing, and deployment to a production environment
• Participating with engineering teams to address any issues in the production pipeline
• Productionizing, auditing, and tracking data science models in an online environment
• Working with Hive or Hadoop, system learning, text mining, and Spark

Preferred Qualifications

* At least a doctorate (PhD) degree in Mathematics, Statistics, or a closely related quantitative field, and at least four (4) years of experience as an information or system learning scientist (any title) including undertaking advanced system learning activities (regression, clustering, and forecasting)

• Using the development and implementation of analytical and data science modeling solutions using techniques such as data mining, system learning, or text mining
• Using mathematical concepts, algorithms, and computational complexity
• Participating with colleagues to bring business value to the organization
• Presenting findings and reports to stakeholders
• Using Python, SQL, R, SAS, risk evaluation, and data manipulation
• Must include at least two (2) years working with large quantities of data and solving business problems
• Working on presenting data science solutions including problem statement, feature engineering, model development, assessment, and testing, and deployment to a production environment
• Participating with engineering teams to address any issues in the production pipeline
• Productionizing, auditing, and tracking data science models in an online environment
• Working with Hive or Hadoop, system learning, text mining, and Spark

Skills and Competencies

* Strong background in mathematics, statistics, or a related quantitative field

• Advanced system learning activities (regression, clustering, and forecasting)
• Development and implementation of analytical and data science modeling solutions
• Mathematical concepts, algorithms, and computational complexity
• Data mining, system learning, or text mining techniques
• Python, SQL, R, SAS, risk evaluation, and data manipulation
• Large quantities of data and solving business problems
• Data science solutions including problem statement, feature engineering, model development, assessment, and testing, and deployment to a production environment
• Hive or Hadoop, system learning, text mining, and Spark

Career Growth Opportunities and Learning Benefits

* arenaflex offers a comprehensive training program to help you develop new skills and advance your career

• Opportunities for professional growth and development in a dynamic and innovative company
• Collaborative and inclusive work environment with a team of experienced professionals
• Flexible work arrangements and remote work options
• Competitive salary and benefits package

Work Environment and Company Culture

* arenaflex is committed to creating a work environment that is collaborative, inclusive, and supportive

• Our team is passionate about using data-driven insights to drive business growth and improve customer experiences
• We value diversity and inclusion and strive to create a workplace that reflects the diversity of our customers and communities
• arenaflex is an equal opportunities employer and welcomes applications from all qualified candidates

Compensation, Perks, and Benefits

* Competitive salary and benefits package

• Flexible work arrangements and remote work options
• Comprehensive training program to help you develop new skills and advance your career
• Opportunities for professional growth and development in a dynamic and innovative company
• Collaborative and inclusive work environment with a team of experienced professionals

How to Apply

If you are a highly skilled and detail-oriented individual with a passion for data analysis and entry, we encourage you to apply for this exciting opportunity to join arenaflex as a Full Stack Data Entry Specialist – Retail Operations and Analytics. Please submit your resume and cover letter to [insert contact information]. We look forward to hearing from you! Apply for this job