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About Arenaflex
At arenaflex, we believe that data is the cornerstone of modern retail innovation. As one of the nation's leading retail organizations, we're transforming how businesses operate by harnessing the power of mathematics, statistics, and cutting-edge machine learning technologies. Our commitment to innovation drives everything we do—from optimizing supply chains to creating personalized shopping experiences for millions of customers across the country.
We are currently seeking a talented and passionate Lead Data Scientist to join our advanced analytics team. In this role, you will be instrumental in building long-term forecasting algorithms that solve complex business challenges in the retail sector. You'll work at the intersection of decision science, machine learning, and operational automation, helping arenaflex stay ahead of industry trends and deliver exceptional value to our stakeholders.
This is a remote-friendly position, allowing you to work from anywhere within the United States while collaborating with talented professionals across our global AI and data science teams.
Position Overview
As a Lead Data Scientist at arenaflex, you will be responsible for leading the design, development, and deployment of sophisticated mathematical and statistical models that drive business decisions. You will transform retail operations by automating processes that currently require manual attention, leveraging your expertise in predictive analytics, time-series forecasting, and machine learning.
You will collect, organize, analyze, interpret, and summarize massive volumes of time-series data to generate actionable insights that lead to innovative applications. Your work will directly impact arenaflex's ability to forecast demand, optimize inventory, and deliver seamless customer experiences.
Key Responsibilities
Your primary responsibilities as a Lead Data Scientist will include:
- Lead the development and enhancement of mathematical and statistical techniques to create long-term forecasting algorithms that solve enterprise-level problems in the retail industry, leveraging deep expertise in decision science methodologies.
- Transform retail operations by automating processes that currently require manual attention and decision-making through advanced mathematics and statistical modeling approaches.
- Collect, organize, analyze, interpret, and summarize large volumes of time-series data to generate key insights leading to new and innovative applications.
- Analyze complex and rich datasets, identify business problems, develop problem statements, define metrics, and drive feasibility studies to validate proposed solutions.
- Perform data exploration tasks, extract meaningful insights, and create compelling storyboards from comprehensive data analysis to present to scientists and leadership teams.
- Present clear and accurate root-cause analysis to examine findings and provide actionable recommendations to stakeholders and executive leadership.
- Build training workflows for machine learning algorithms operating on tens of millions of data points, creating algorithmic solutions including data understanding, 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 and identify improvements to enhance accuracy, efficiency, and business impact of deployed models.
- Collaborate with global AI teams, scientists, engineers, and business partners to identify and lead new opportunities for innovation and value creation.
- Advocate for best software engineering practices and capable of prototyping individual components of data science solutions.
Required Skills & Competencies
To succeed in this role, you must possess a strong foundation in the following areas:
- Machine Learning: Extensive experience with advanced machine learning activities including regression, clustering, and forecasting techniques.
- Statistical Analysis: Deep understanding of probability theory, statistics, and mathematical concepts applied to real-world business problems.
- Optimization Theory: Knowledge of optimization techniques including linear programming, integer programming, and combinatorial optimization.
- Deep Learning: Familiarity with neural network architectures and deep learning frameworks.
- Data Pipeline Engineering: Experience building and maintaining scalable data pipelines and distributed systems.
- Database Architecture: Strong understanding of database design, SQL, and NoSQL systems.
- Programming Languages: Proficiency in Python, R, SQL, SAS, Spark, Scala, Java, JavaScript, C, HTML, MATLAB, and Command Shell scripting.
- Big Data Technologies: Experience with Hadoop, Hive, and distributed computing frameworks.
- Text Mining: Capability to extract insights from unstructured text data using natural language processing techniques.
- Communication Skills: Ability to present complex technical findings to non-technical stakeholders clearly and persuasively.
Educational & Experience Requirements
Option 1: Master's Degree Path
Candidates must have:
- At least a Master's degree in Mathematics, Statistics, or a closely related quantitative field.
- A minimum of seven (7) years of experience as a data or machine learning scientist (any title).
- Experience undertaking advanced machine learning activities including regression, clustering, and forecasting.
- Experience using the development and implementation of analytical and data science modeling answers using strategies including data mining, machine learning, or text mining.
- Proficiency in applying mathematical concepts, algorithms, and computational complexity analysis.
- Experience collaborating with colleagues to deliver business value to the organization.
- Experience providing findings and reports to stakeholders.
- Strong skills in Python, SQL, R, SAS, risk assessment, and data manipulation.
- At least two (2) years of experience working with large volumes of data and solving complex business problems.
- Experience delivering data science solutions including problem statement definition, feature engineering, model development, evaluation and testing, and deployment to production environments.
- Experience collaborating with engineering teams to address production pipeline issues.
- Experience productionizing, auditing, and monitoring data science models in online environments.
- Working experience with Hive or Hadoop, machine learning, text mining, and Spark.
Option 2: PhD Path
Alternatively, the company will accept:
- At least a Doctorate (PhD) in Mathematics, Statistics, or a closely related quantitative field.
- A minimum of four (4) years of experience as a data or machine learning scientist (any title).
- All other requirements listed above for Option 1.
Career Growth & Learning Opportunities
At arenaflex, we invest in the professional development of our team members. As a Lead Data Scientist, you will have access to:
- Advanced Training Programs: Opportunities to attend conferences, workshops, and certification programs in cutting-edge data science methodologies.
- Mentorship Opportunities: Work alongside experienced data scientists and AI researchers who will help guide your career progression.
- Cross-Functional Collaboration: Engage with teams across engineering, product, and business domains to broaden your expertise.
- Research & Innovation: Ability to explore new methodologies and contribute to arenaflex's thought leadership in the retail analytics space.
- Leadership Development: Clear pathways to advance into senior technical leadership or management roles based on your career aspirations.
Work Environment & Culture
Arenaflex fosters a collaborative, inclusive, and innovation-driven work environment. We value diversity of thought and encourage creative problem-solving. Our remote-friendly policy allows you to maintain work-life balance while staying connected with your team through advanced collaboration tools.
You'll be joining a team of passionate data scientists, engineers, and business experts who are committed to transforming the retail industry through data-driven innovation. We celebrate achievements, support continuous learning, and maintain an open-door policy where every voice matters.
Compensation & Benefits
Arenaflex offers a competitive compensation package that includes:
- Salary Range: $35 to $50 per hour, commensurate with experience and qualifications.
- Health & Wellness: Comprehensive health, dental, and vision insurance plans.
- Retirement Plans: 401(k) matching and retirement savings programs.
- Paid Time Off: Generous vacation, sick leave, and personal days.
- Professional Development: Tuition reimbursement and continuing education support.
- Remote Work Benefits: Home office stipend and flexible scheduling.
- Employee Discounts: Exclusive discounts on arenaflex products and services.
Join Our Team
Are you ready to make a meaningful impact in the retail industry through data science? Do you thrive on solving complex problems and building solutions that transform how businesses operate? If so, we invite you to apply for the Lead Data Scientist position at arenaflex.
This is your opportunity to join a forward-thinking organization that values innovation, collaboration, and excellence. You'll work on challenging projects that push the boundaries of what's possible in retail analytics, all while growing your career alongside talented professionals.
Apply now and become part of a team that's shaping the future of retail through the power of data and machine learning. We look forward to welcoming you to arenaflex!
Note: This position is remote-friendly and allows telecommuting from any location within the United States.