Senior Staff Data Scientist – Remote Data Engineering & Business Insight Leadership at arenaflex

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Why Join arenaflex?

arenaflex is redefining the future of retail through data‑driven innovation. With a massive
footprint across the United States, arenaflex operates a sophisticated ecosystem of physical
stores, e‑commerce platforms, mobile apps, and a global supply chain. Our mission is simple:
help people save money and live better. To achieve that, we invest heavily in
cutting‑edge analytics, AI, and machine‑learning solutions that turn billions of data points
into actionable insights for customers, merchants, and internal teams. As a remote‑first
organization, arenaflex empowers its talent to work from anywhere while fostering a collaborative
culture built on curiosity, responsibility, and continuous learning.

Position Overview

arenaflex is seeking a highly experienced Senior Staff Data Scientist to lead
the technical vision for our Data Products line within the Data Services team. In this
remote role, you will act as the tech lead for all data‑technology initiatives, shape
customer‑centric data science projects, mentor junior colleagues, and champion best
practices across the organization. You will work directly with business stakeholders
to translate complex challenges into scalable, high‑impact solutions that drive
omnichannel performance.

Key Responsibilities

Data Source Identification & Acquisition

• Collaborate with product owners to define data‑requirements and service‑level agreements.


• Identify, evaluate, and ingest optimal data sources—including third‑party feeds—to
  support analytical objectives.


• Perform initial data quality assessments and ensure data is fit‑for‑purpose.


• Review deliverables from junior team members, providing constructive feedback and
  guidance on improvement.

Problem Formulation & Business Impact

• Deep‑dive into business problems, challenging assumptions to uncover root causes.


• Define clear analytics, machine‑learning, and automation goals aligned with
  arenaflex’s strategic metrics.


• Quantify expected business impact (e.g., revenue lift, cost reduction, customer
  satisfaction) and communicate these forecasts to leadership.

Analytical Modeling & Experimentation

• Select and tailor modeling strategies for complex, large‑scale, multi‑modal data
  environments.


• Iteratively develop features and models in partnership with domain experts.


• Conduct exploratory data analysis, hypothesis testing, and statistical inference to
  validate assumptions.


• Design experiments, A/B tests, and validation frameworks that drive data‑backed
  decision making.


• Prototype and iterate on advanced techniques such as deep learning, reinforcement
  learning, and generative AI to address novel challenges.


• Guide the team on feature engineering, experiment design, and state‑of‑the‑art
  modeling for unstructured and streaming data.

Model Deployment, Scaling & MLOps

• Partner with the MLOps engineering group to move models from prototype to production
  at scale.


• Implement continuous monitoring, logging, and performance tracking against defined
  KPIs.


• Diagnose drift, latency, and scalability issues; iterate on model parameters as
  needed.


• Maintain robust CI/CD pipelines, code documentation, and playbooks for reproducibility.

Software Development & Testing

• Write clean, production‑ready code in Python, R, or other appropriate languages.


• Develop unit and integration tests, proof‑of‑concept implementations, and
  validation suites to ensure solution reliability.


• Contribute to shared libraries, SDKs, and internal tools that accelerate data
  product delivery.

Business Acumen & Stakeholder Influence

• Translate technical concepts into clear, business‑focused narratives for executives
  and cross‑functional partners.


• Build compelling business cases, ROI analyses, and funding proposals that align with
  arenaflex’s strategic priorities.


• Challenge existing assumptions and introduce innovative, enterprise‑wide approaches
  to data utilization.


• Mentor peers on best practices, fostering a culture of data literacy and ethical AI
  usage.

Model Evaluation & Validation

• Define rigorous evaluation metrics tailored to each analytical objective.


• Apply robust testing and tuning strategies to assess model accuracy, fairness,
  robustness, and compliance.


• Document testing procedures and maintain a living repository of validation results.

Data Visualization & Storytelling

• Select the most effective visualization tools (e.g., Tableau, PowerBI, custom D3.js
  dashboards) based on audience and context.


• Craft intuitive visual narratives that turn complex data sets into actionable
  insights.


• Collaborate with UX/UI designers to embed analytical outputs into front‑end
  applications.


• Tailor communication style to diverse stakeholder groups, driving informed
  decision‑making and behavioral change.


• Coach junior teammates on storytelling frameworks, ensuring consistency and impact
  across all deliverables.

Essential Qualifications

• Education: Bachelor’s degree in Statistics, Mathematics, Computer
  Science, Economics, Engineering, or a related quantitative discipline (Master’s or Ph.D.
  preferred).


• Experience: Minimum 4 years of hands‑on experience in data science,
  analytics, or machine learning within a fast‑paced, large‑scale environment.


• Technical Skills: Proficiency in Python and/or R; strong grasp of
  SQL, data pipelines (e.g., Airflow, Prefect), and cloud platforms (AWS, GCP, Azure).


• Machine Learning Expertise: Deep knowledge of supervised/unsupervised
  learning, deep learning frameworks (TensorFlow, PyTorch), and MLOps best practices.


• Statistical Foundations: Ability to conduct hypothesis testing,
  experimental design, and causal inference with rigor.


• Communication: Proven ability to distill complex technical concepts
  into clear, business‑oriented language for executives and non‑technical partners.


• Leadership: Experience mentoring junior data scientists and leading
  cross‑functional project teams.

Preferred Qualifications & Nice‑to‑Have Skills

• Advanced degree (Master’s or Ph.D.) in a quantitative field.


• Experience with big‑data technologies such as Spark, Hadoop, or Flink.


• Familiarity with real‑time streaming analytics (Kafka, Kinesis).


• Exposure to computer vision, NLP, or reinforcement learning applications.


• Track record of delivering production‑grade ML models that generate measurable
  business value.


• Knowledge of data governance, privacy regulations (GDPR, CCPA) and ethical AI
  principles.


• Previous experience in retail, e‑commerce, or consumer‑goods industries.

Core Competencies for Success

• Strategic Thinking: Ability to see the big picture while executing
  detailed technical work.


• Problem Solving: Analytical mindset, curiosity, and persistence in
  tackling ambiguous problems.


• Collaboration: Works effectively across product, engineering,
  operations, and business teams in a remote setting.


• Adaptability: Thrives in a fast‑changing environment, quickly adopting
  new tools and methodologies.


• Ownership: Takes end‑to‑end responsibility for delivering high‑impact
  solutions on schedule.

Career Growth & Learning Opportunities

At arenaflex, your development is a priority. As a Senior Staff Data Scientist you will
have access to:

• Mentorship programs with senior leaders across AI/ML, product, and business domains.


• Tuition reimbursement for advanced degrees, certifications, and industry conferences.


• Internal training labs featuring the latest tools—Cloud AI platforms, AutoML, and
  emerging research.


• Opportunities to lead high‑visibility, enterprise‑wide initiatives that shape the
  future of retail analytics.


• A clear promotion pathway from Staff to Principal and Distinguished Data Scientist
  roles.

Work Environment & Culture at arenaflex

arenaflex cultivates a supportive, inclusive, and innovative culture where every voice
matters. Our remote‑first model is backed by:

• Flexible work hours and a robust virtual collaboration suite (Slack, Teams, Miro).


• Regular virtual “coffee chats,” hackathons, and knowledge‑sharing sessions.


• Diversity, equity, and inclusion (DEI) initiatives that empower underrepresented
  talent.


• Employee resource groups focused on technology, sustainability, and community
  impact.


• A commitment to work‑life balance, with generous paid time off and parental leave.

Compensation, Perks & Benefits

arenaflex offers a competitive hourly rate of $30‑$40 per hour plus a comprehensive
benefits package designed for you and your family:

• Medical, vision, and dental plans with options for dependents.


• 401(k) with company match, employee stock purchase plan, and life insurance.


• Employee discounts – both in‑store and online.


• Education assistance for yourself and eligible dependents.


• Paid parental leave, short‑ and long‑term disability, and paid time off (vacation,
  sick, personal days).


• Wellness programs, mental‑health resources, and virtual fitness classes.

How to Apply

If you are ready to lead groundbreaking data initiatives and make a measurable impact on
the future of retail, we want to hear from you. Join arenaflex’s mission‑driven team and
help millions of shoppers worldwide save money and live better.

Apply Now

Apply Now