Senior Data Science Analyst – Advanced Recommendation Systems, A/B Testing, Machine Learning & Analytics at arenaflex (Remote – Boston, USA)

About arenaflex – Pioneering the Future of E‑Commerce Analytics

arenaflex is a global leader in online retail, renowned for turning massive data streams into actionable insights that shape the shopping experience of millions worldwide. Our mission is to blend cutting‑edge technology with deep consumer understanding, delivering personalized product recommendations that feel intuitive, relevant, and delightful. As a data‑driven organization, we invest heavily in research, experimentation, and innovation, fostering an environment where curiosity thrives and bold ideas become reality.

Why This Role Matters

At arenaflex, the Senior Data Science Analyst sits at the heart of our Research & Recommendations Lab. This team is responsible for designing, testing, and refining the algorithms that power the next generation of product suggestions. Your work will directly influence the shopping journey of our customers, driving higher engagement, conversion, and satisfaction across all touchpoints.

Key Responsibilities

• Design, implement, and evaluate A/B experiments for new recommendation algorithms, ensuring rigorous statistical validity and clear business impact.
• Develop and maintain KPI dashboards, incorporating anomaly detection tools and high‑level forecasting models to monitor system health in real time.
• Conduct exploratory data analysis (clustering, segmentation, dimensionality reduction) to uncover hidden patterns and generate fresh product recommendation strategies.
• Build, maintain, and enhance internal automation tools—including a custom QA framework—to simulate algorithm performance before live deployment.
• Lead end‑to‑end data pipelines: from raw data extraction, cleaning, and feature engineering to model training, validation, and production rollout.
• Collaborate closely with product managers, UI/UX designers, and AI engineers to translate business goals into technical specifications.
• Communicate findings and strategic recommendations to senior leadership across product, engineering, and marketing teams, using clear visualizations and concise narratives.
• Mentor junior analysts and data scientists, fostering a culture of continuous learning and knowledge sharing.

Essential Qualifications

• Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field (Master’s or Ph.D. preferred).
• Technical Expertise: Advanced proficiency in SQL (complex queries, stored procedures, string parsing, Vertica/Hive/Presto/BigQuery).
• Programming Skills: Deep experience with Python and its data‑science ecosystem (Jupyter notebooks, pandas, NumPy, scikit‑learn, matplotlib, seaborn, PySpark).
• Statistical Foundations: Strong background in experimental design, hypothesis testing, and causal inference for A/B testing.
• Machine Learning Knowledge: Hands‑on experience with decision trees, random forests, gradient boosting, deep learning (TensorFlow/PyTorch) in a production setting.
• Communication: Excellent written and verbal communication skills; ability to convey complex technical concepts to non‑technical stakeholders.
• Collaboration: Proven ability to work cross‑functionally, building strong relationships with product, engineering, and design teams.
• Ownership & Impact: Demonstrated track record of taking initiative, driving projects to completion, and delivering measurable business outcomes.

Preferred Qualifications & Experience

• Master’s or Ph.D. in a quantitative discipline with a focus on machine learning or econometrics.
• Experience in e‑commerce or online retail analytics, especially in recommendation systems.
• Familiarity with big‑data platforms (Spark, Hadoop) and cloud services (AWS, GCP, Azure).
• Knowledge of modern experimentation frameworks (e.g., Optimizely, LaunchDarkly) and feature flagging systems.
• Publications or conference presentations in data science, machine learning, or related fields.
• Exposure to MLOps practices: model versioning, CI/CD pipelines, monitoring, and automated rollback mechanisms.

Core Skills & Competencies

• Analytical Thinking: Ability to dissect complex problems, identify root causes, and propose data‑driven solutions.
• Problem‑Solving: Comfortable navigating ambiguous situations and iterating quickly based on feedback.
• Attention to Detail: Rigorous approach to data quality, experiment design, and reproducibility.
• Leadership: Proactive in influencing stakeholders, championing best practices, and mentoring peers.
• Adaptability: Thrive in a fast‑paced environment where priorities shift and new challenges emerge daily.
• Ethical Mindset: Commitment to responsible AI, data privacy, and fairness in algorithmic decision‑making.

Career Growth & Learning Opportunities

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

• Annual learning stipend for conferences, certifications, or advanced coursework.
• Internal mentorship programs pairing you with senior leaders in AI, product, and engineering.
• Opportunities to lead high‑visibility projects that directly influence company strategy.
• Cross‑functional rotations to broaden your expertise across product, marketing, and operations.
• Regular hackathons and innovation days where you can experiment with emerging technologies.

Work Environment & Culture at arenaflex

Our culture is built on three pillars: Innovation, Inclusion, and Impact.

• Innovation: We encourage curiosity, provide sandbox environments, and celebrate calculated risk‑taking.
• Inclusion: arenaflex is committed to equal opportunity for all, including individuals with disabilities. We provide reasonable accommodations and foster a supportive, diverse community.
• Impact: Every line of code, every model, and every insight you produce contributes to a tangible improvement in the customer experience.

Our remote‑first policy allows you to work from anywhere in the Boston metropolitan area (or any location you prefer, subject to occasional in‑person collaboration days). Flexible hours, generous PTO, and a collaborative Slack community keep you connected while respecting work‑life balance.

Compensation, Perks & Benefits

• Competitive hourly rate ranging from $20–$30, commensurate with experience and expertise.
• Comprehensive health, dental, and vision insurance plans.
• 401(k) matching and financial wellness programs.
• Generous paid time off, parental leave, and holiday schedule.
• Wellness stipend, virtual fitness classes, and mental‑health resources.
• Employee assistance program and disability accommodations.
• Technology allowance for home office setup (monitor, ergonomic chair, etc.).

How to Apply

If you are passionate about turning data into strategic advantage and want to shape the future of online retail at a world‑class organization, we want to hear from you. Click the link below to submit your application, resume, and a brief cover letter highlighting your most relevant experience.

Apply!

Join arenaflex – Where Data Meets Delight

At arenaflex, your analytical expertise will not only drive business results but also enhance the everyday shopping journey for millions of customers. We value curiosity, collaboration, and a relentless drive for excellence. Take the next step in your career and become part of a team that is redefining the e‑commerce landscape—one insight at a time.