Lead Data Scientist – Advanced Machine Learning & Forecasting for Retail Innovation (Remote – USA)

About arenaflex

arenaflex is a forward‑thinking leader in the retail technology space, dedicated to transforming how millions of shoppers experience commerce every day. With a deep commitment to data‑driven decision making, arenaflex empowers its partners to anticipate demand, optimize inventory, and deliver personalized experiences at scale. Our mission is to blend cutting‑edge artificial intelligence with real‑world retail challenges, creating solutions that are both innovative and practical. As a fully remote‑first organization, arenaflex attracts top talent from across the United States, fostering a collaborative, inclusive, and high‑performance culture that thrives on curiosity, continuous learning, and impact.

Why This Role Matters

Retail is evolving faster than ever, and the ability to predict trends, manage supply chains, and personalize offers is a competitive advantage. As the Lead Data Scientist at arenaflex, you will spearhead the design, development, and deployment of sophisticated forecasting algorithms that solve complex business problems. Your work will directly influence product strategy, operational efficiency, and revenue growth, positioning arenaflex as the go‑to partner for retailers seeking data‑powered transformation.

Key Responsibilities

• Architect and implement long‑term forecasting models that address critical retail challenges such as demand planning, stock‑outs, and promotional effectiveness.
• Automate manual analytics workflows by translating business logic into robust statistical and machine‑learning pipelines.
• Collect, clean, and curate massive time‑series datasets, ensuring data quality and consistency for downstream modeling.
• Perform exploratory data analysis (EDA) to uncover hidden patterns, generate actionable insights, and communicate findings to stakeholders.
• Define problem statements, design metrics, and conduct feasibility studies that align with strategic objectives.
• Build end‑to‑end machine‑learning pipelines—including feature engineering, model training, validation, and production deployment—using tools such as Python, Spark, and Hadoop.
• Lead large‑scale implementation of ML models across diverse retail data sources, monitoring performance and iterating for continuous improvement.
• Collaborate closely with global AI teams, data engineers, product managers, and business partners to identify new opportunities and translate them into scalable solutions.
• Advocate for best practices in software engineering, reproducibility, and model governance, ensuring that every solution is production‑ready and auditable.
• Mentor junior data scientists and analysts, fostering a culture of knowledge sharing and technical excellence.

Essential Qualifications

• Master’s degree in Mathematics, Statistics, Computer Science, or a closely related quantitative field.
• Minimum 7 years of professional experience as a data scientist or machine‑learning engineer, with a proven track record of delivering high‑impact predictive models (regression, clustering, forecasting).
• Demonstrated expertise in statistical modeling, algorithm design, and computational complexity analysis.
• Hands‑on experience with large‑scale data processing frameworks (Hadoop, Hive, Spark) and distributed computing environments.
• Proficiency in Python, SQL, R, and at least one of the following: SAS, Scala, Java, or C.
• Strong background in data mining, text analytics, and feature engineering for high‑dimensional datasets.
• Experience deploying models to production, including monitoring, versioning, and performance optimization.
• Excellent communication skills, with the ability to translate technical results into clear business recommendations for senior leadership.
• Eligibility to work remotely from any location within the United States.

Preferred Qualifications

• Ph.D. in Mathematics, Statistics, or a related quantitative discipline.
• At least 4 years of experience leading end‑to‑end machine‑learning projects in a retail or e‑commerce environment.
• Deep familiarity with deep learning frameworks (TensorFlow, PyTorch) and advanced optimization techniques.
• Experience with cloud platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
• Background in operations research, linear programming, or stochastic modeling.
• Published research or patents in the field of predictive analytics or AI for retail.

Core Skills & Competencies

• Analytical Thinking: Ability to dissect complex problems, formulate hypotheses, and test them rigorously.
• Programming Mastery: Clean, maintainable code in Python and SQL; familiarity with version control (Git).
• Statistical Rigor: Expertise in hypothesis testing, Bayesian methods, and multivariate analysis.
• Collaboration: Proven experience working in cross‑functional teams, influencing product roadmaps, and driving consensus.
• Leadership: Capacity to lead projects, mentor peers, and champion data‑centric culture.
• Business Acumen: Understanding of retail operations, supply chain dynamics, and revenue drivers.
• Adaptability: Comfort with fast‑paced environments, evolving requirements, and emerging technologies.

Career Growth & Learning Opportunities

arenaflex invests heavily in the professional development of its team members. As a Lead Data Scientist, you will have access to:

• Annual learning stipend for conferences, certifications, or advanced coursework.
• Mentorship programs pairing you with senior AI architects and industry experts.
• Opportunities to publish internal whitepapers, present at industry forums, and contribute to open‑source projects.
• Clear promotion pathways—from Lead to Principal Scientist, and eventually to Director of AI & Analytics.
• Cross‑functional rotations that broaden exposure to product management, engineering, and go‑to‑market teams.

Work Environment & Culture at arenaflex

Our remote‑first model is built on trust, flexibility, and results‑orientation. Key cultural pillars include:

• Inclusivity: Diverse perspectives are celebrated; we provide accommodations and resources for all team members.
• Innovation: Regular hackathons, idea incubators, and “innovation days” encourage creative problem‑solving.
• Transparency: Weekly all‑hands, open‑door leadership, and clear OKRs keep everyone aligned.
• Well‑Being: Comprehensive mental‑health support, flexible schedules, and a generous PTO policy.
• Collaboration: State‑of‑the‑art virtual collaboration tools, quarterly in‑person meet‑ups, and team‑building retreats.

Compensation, Perks & Benefits

arenaflex offers a competitive compensation package that reflects the expertise required for this role:

• Hourly rate ranging from $35 to $50 per hour, commensurate with experience and qualifications.
• Performance‑based bonuses tied to project milestones and business impact.
• Full health, dental, and vision coverage for you and eligible dependents.
• 401(k) plan with company match.
• Remote‑work allowance covering home‑office equipment, high‑speed internet, and ergonomic accessories.
• Generous paid time off, parental leave, and sabbatical options.
• Access to a learning platform (e.g., Coursera, Udacity) and a library of technical resources.

How to Apply

If you are passionate about turning massive retail data into strategic advantage and thrive in a collaborative, remote environment, we want to hear from you. To apply, please click the link below, submit your resume, and include a brief cover letter highlighting a recent forecasting project you led.

Apply Now – Join arenaflex

Closing Statement

arenaflex is on a mission to redefine retail through intelligent automation and predictive insight. As the Lead Data Scientist, you will be at the heart of this transformation, shaping the future of commerce for millions of customers. Take the next step in your career and become part of a visionary team that values expertise, creativity, and impact. Apply today and help us build the next generation of retail intelligence.