About careerzynith
careerzynith is a forward‑thinking leader in the health‑care technology space, dedicated to transforming the way health‑services organizations manage their IT operations and deliver care. Our mission‑driven team builds cutting‑edge AIOps platforms that empower enterprises to anticipate issues, automate resolutions, and continuously improve service reliability. As a part of careerzynith, you will join a vibrant, high‑velocity environment where innovation meets impact, and where every line of code contributes to the well‑being of millions of users worldwide.
Why This Role Matters
In today’s data‑rich landscape, the ability to turn massive streams of operational data into actionable insights is a competitive advantage. careerzynith’s AI‑powered platform sits at the heart of this transformation, leveraging advanced machine learning, deep learning, and statistical modeling to predict outages, detect anomalies, and recommend proactive fixes before they affect end‑users. As a Part‑Time Remote Data Scientist, you will be a key architect of these intelligent solutions, shaping the future of automated IT operations for a leading health‑care technology provider.
Key Responsibilities
- Collaborate with cross‑functional engineers, product managers, and domain experts to design, develop, and scale AI and machine‑learning solutions that monitor and optimize large‑scale IT infrastructures.
- Build, train, and evaluate predictive models using techniques such as supervised learning, unsupervised clustering, time‑series forecasting, and deep learning to detect performance degradation, hardware failures, and security incidents.
- Develop robust data pipelines that ingest, cleanse, and transform high‑velocity telemetry data from diverse sources, ensuring data quality and consistency for downstream analytics.
- Integrate AI models into careerzynith’s production environment, working closely with DevOps teams to containerize, orchestrate, and monitor model performance at scale.
- Document model architecture, data schemas, experiment results, and operational procedures to facilitate knowledge sharing and reproducibility across the organization.
- Participate in code reviews, pair‑programming sessions, and technical workshops to foster a collaborative learning culture.
- Stay abreast of emerging AI/ML research, tools, and best practices, and proactively propose enhancements that keep careerzynith at the forefront of technology.
- Provide mentorship and technical guidance to junior data scientists and analysts, helping them grow their skill sets and contribute effectively to project goals.
Essential Qualifications
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline (or equivalent practical experience).
- Minimum of 2 years of hands‑on experience applying AI/ML techniques to real‑world problems, with a focus on data‑driven statistical modeling, classification, regression, or anomaly detection.
- Proficiency in at least one programming language commonly used for data science, such as Python or R, and strong command of SQL for data extraction and manipulation.
- Demonstrated experience in building end‑to‑end data pipelines, including data ingestion, preprocessing, feature engineering, and storage.
- Solid understanding of machine‑learning concepts, including model evaluation metrics, cross‑validation, hyperparameter tuning, and model deployment strategies.
- Excellent verbal and written communication skills, with the ability to translate complex technical concepts into clear, actionable insights for both technical and non‑technical stakeholders.
- Strong problem‑solving mindset, attention to detail, and a proactive attitude toward delivering high‑quality results on schedule.
Preferred Qualifications & Additional Skills
- Advanced degree (M.S. or Ph.D.) in a quantitative field such as Statistics, Applied Mathematics, Computer Science, or a related discipline.
- Experience working with large‑scale cloud data platforms (e.g., careerzynith, careerzynith) and distributed processing frameworks such as Apache Spark or Hadoop.
- Hands‑on experience developing and deploying production‑grade AI models using containerization technologies (Docker, Kubernetes) and CI/CD pipelines.
- Familiarity with time‑series analysis, signal processing, and forecasting methods applied to infrastructure telemetry data.
- Track record of designing scalable, reusable AI components that have been adopted across multiple product lines or business units.
- Knowledge of AIOps concepts, IT service management (ITSM) processes, and the operational challenges faced by large health‑care organizations.
- Ability to mentor peers, lead technical discussions, and contribute to a culture of continuous learning and knowledge sharing.
Core Skills & Competencies
- Analytical Thinking: Ability to dissect complex datasets, identify patterns, and derive meaningful insights that drive business value.
- Collaboration: Comfortable working in a remote, distributed team environment, building strong relationships with engineers, product owners, and domain experts.
- Communication: Clear articulation of technical findings, creation of concise documentation, and effective presentation of results to diverse audiences.
- Adaptability: Thrive in a fast‑paced, ever‑changing environment, quickly learning new tools, frameworks, and domain knowledge.
- Innovation: Passion for exploring novel AI techniques, experimenting with cutting‑edge research, and translating ideas into production‑ready solutions.
- Ownership: Take end‑to‑end responsibility for model lifecycle—from conception through deployment, monitoring, and continuous improvement.
Career Growth & Learning Opportunities
careerzynith invests heavily in the professional development of its team members. As a part‑time data scientist, you will have access to:
- Mentorship from senior AI architects and industry veterans who have built large‑scale predictive platforms.
- Sponsored attendance at leading conferences (e.g., NeurIPS, KDD, Strata Data) and access to premium online courses on advanced machine learning, cloud engineering, and data engineering.
- Opportunities to lead high‑impact projects, influence product roadmaps, and shape the strategic direction of careerzynith’s AI initiatives.
- A clear promotion pathway that recognizes technical expertise, leadership, and impact, with titles ranging from Data Scientist I to Senior Principal Data Scientist.
- Cross‑functional rotations that allow you to gain exposure to product management, engineering, and operations, broadening your skill set and career horizons.
Work Environment & Culture at careerzynith
Our culture is built on three pillars: Innovation, Collaboration, and Well‑Being. We foster an inclusive environment where diverse perspectives are celebrated, and every team member is encouraged to voice ideas. Remote work is a core part of our model—our employees enjoy flexible schedules, a results‑oriented approach, and a supportive community that values work‑life balance. Regular virtual coffee chats, hackathons, and wellness programs keep the team connected and energized.
Compensation, Perks & Benefits
careerzynith offers a competitive hourly rate of $25 per hour for part‑time contributors, along with a comprehensive benefits package that includes:
- Health, dental, and vision insurance options.
- Retirement savings plan with company matching.
- Paid time off, holidays, and flexible scheduling to accommodate personal commitments.
- Professional development stipend for courses, certifications, and conference attendance.
- Access to cutting‑edge cloud resources and AI tooling to accelerate your experiments.
- Employee assistance programs focused on mental health, financial wellness, and family support.
How to Apply
If you are passionate about turning massive streams of operational data into intelligent, proactive solutions, and you thrive in a collaborative, remote‑first environment, we want to hear from you. Join careerzynith’s mission‑driven team and help shape the future of AI‑powered IT operations.
Closing Statement
careerzynith is committed to building a diverse workforce that reflects the communities we serve. We encourage candidates of all backgrounds to apply. Take the next step in your career and become part of a team that is redefining how technology supports health‑care excellence.