Senior Software/Data Science Engineer – Manufacturing Data Analytics (Remote, Part/Full‑Time) – arenaflex
About arenaflex – Pioneering the Future of Manufacturing Intelligence
arenaflex is a global leader in innovative technology solutions, delivering cutting‑edge products and services that empower manufacturers worldwide. Our mission is to transform raw data into actionable insights, enabling smarter decision‑making, higher efficiency, and unparalleled product quality. As a remote‑first organization, arenaflex embraces flexibility, diversity, and continuous learning, offering a collaborative environment where talented professionals can thrive from anywhere in the world.
Why This Role Matters
In today’s hyper‑connected manufacturing landscape, the ability to collect, analyze, and act on massive streams of data is a competitive advantage. As a Senior Software/Data Science Engineer on our Manufacturing Data Analytics team, you will be at the heart of this transformation. You will design, build, and scale sophisticated data pipelines and machine‑learning models that power real‑time quality assurance, predictive maintenance, and process optimization across arenaflex’s extensive device ecosystem.
Key Responsibilities
Working closely with product owners, data scientists, and cross‑functional teams, you will be responsible for the end‑to‑end delivery of data‑driven solutions. Your day‑to‑day activities will include:
- Architecting Scalable Data Solutions: Design and implement robust data ingestion, storage, and processing pipelines on AWS services, ensuring high availability and low latency for millions of data points per day.
- Machine Learning & AI Development: Lead the creation of advanced AI/ML models—including natural language processing, anomaly detection, and predictive analytics—to extract insights from raw manufacturing data.
- Model Deployment & Monitoring: Build production‑ready ML pipelines, automate model training, and establish monitoring dashboards to track model performance and drift.
- Collaboration & Requirement Gathering: Partner with internal stakeholders to translate business needs into technical specifications, write detailed design documents, and prioritize feature backlogs.
- Code Quality & Review: Conduct rigorous code reviews, enforce best practices, and mentor junior engineers on clean coding, testing, and version control.
- Continuous Improvement: Participate in agile ceremonies, provide feedback on process enhancements, and drive initiatives that increase the efficiency of the data analytics lifecycle.
- Leadership & Mentorship: Coach and develop other software engineers, fostering a culture of knowledge sharing and technical excellence.
Essential Qualifications
To succeed in this role, you should bring a blend of technical depth, analytical mindset, and collaborative spirit. The following qualifications are required:
- Minimum 5 years of professional software development experience, with at least 3 years focused on data‑intensive applications.
- Proficiency in Python and SQL, as well as experience with RESTful APIs, HTML, and modern web technologies.
- Strong foundation in machine learning, statistical process control (SPC), and AI/ML frameworks such as TensorFlow, PyTorch, or Scikit‑Learn.
- Hands‑on experience designing and deploying solutions on AWS (e.g., S3, Lambda, Glue, Redshift, SageMaker).
- Demonstrated ability to lead complex projects from concept through production, including architecture, scalability, and reliability considerations.
- Excellent written and verbal communication skills, with a proven track record of collaborating across distributed teams.
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related field.
Preferred Qualifications & Additional Skills
- Experience with full software development lifecycle (SDLC) practices: coding standards, code reviews, source‑control (Git), CI/CD pipelines, automated testing, and release management.
- Background in manufacturing, industrial IoT, or supply‑chain analytics, providing domain‑specific insight into production data challenges.
- Leadership experience as a technical lead, mentor, or team manager, guiding multi‑disciplinary engineering groups.
- Familiarity with containerization (Docker, Kubernetes) and infrastructure‑as‑code tools (Terraform, CloudFormation).
- Advanced degree (M.S. or Ph.D.) in Computer Science, Data Science, or a related discipline.
Core Skills & Competencies
- Analytical Thinking: Ability to dissect complex data problems, formulate hypotheses, and develop data‑driven solutions.
- Problem‑Solving: Creative approach to troubleshooting, debugging, and optimizing large‑scale systems.
- Collaboration: Comfortable working in a remote, multicultural environment, building strong relationships with peers and stakeholders.
- Adaptability: Thrive in a fast‑moving, ever‑evolving tech landscape, quickly mastering new tools and methodologies.
- Leadership: Inspire and develop junior talent, fostering a culture of continuous learning and excellence.
Career Growth & Learning Opportunities
arenaflex invests heavily in the professional development of its employees. In this role, you will have access to:
- Mentorship from senior architects and data science leaders.
- Sponsored certifications and training programs in cloud technologies, AI/ML, and advanced analytics.
- Opportunities to present at internal tech talks, industry conferences, and publish research papers.
- A clear career ladder—from senior engineer to principal engineer, and eventually to technical leadership or product management pathways.
- Cross‑functional project exposure, allowing you to broaden your expertise beyond data engineering into product strategy and business operations.
Work Environment & Culture at arenaflex
Our remote‑first philosophy means you can work from any location in the Philippines—or anywhere else—while staying tightly connected to a vibrant, supportive community. arenaflex values:
- Diversity & Inclusion: A workplace where every voice is heard, regardless of background, gender identity, sexual orientation, veteran status, or ability.
- Innovation: A culture that encourages experimentation, rapid prototyping, and learning from failure.
- Collaboration: Regular virtual coffee chats, team‑building activities, and open‑door communication channels with leadership.
- Work‑Life Balance: Flexible hours, generous paid time off, and a supportive environment for students balancing coursework and professional growth.
Compensation, Perks & Benefits
arenaflex offers a competitive salary range of $35,000–$45,000 per year, commensurate with experience and expertise. In addition to base compensation, you will enjoy:
- Performance‑based bonuses and stock‑option opportunities.
- Comprehensive health, dental, and vision insurance plans.
- Retirement savings plans with company matching contributions.
- Professional development stipend for courses, conferences, and certifications.
- Home office allowance to set up an ergonomic remote workspace.
- Paid parental leave, wellness programs, and employee assistance resources.
How to Apply
If you are passionate about turning raw manufacturing data into strategic intelligence and want to grow your career within a forward‑thinking, inclusive organization, we want to hear from you. Click the link below to submit your application, resume, and a brief cover letter outlining why you are the perfect fit for this role at arenaflex.
Apply Now – Join arenaflex!
Closing Statement
At arenaflex, you will be part of a tight‑knit team of eight engineers dedicated to delivering reliable, high‑quality solutions that power the next generation of manufacturing devices. Your contributions will directly influence product quality, operational efficiency, and the overall success of our global customers. We celebrate curiosity, continuous improvement, and the power of data to drive meaningful change. Take the next step in your career—apply today and help shape the future of manufacturing intelligence with arenaflex.
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