About careerzynith
careerzynith is a leading innovator in the health‑technology space, dedicated to transforming the way healthcare organizations manage and protect their digital infrastructure. With a mission to empower the CVS Wellbeing ecosystem through cutting‑edge AI and machine‑learning solutions, careerzynith blends deep industry expertise with a culture of rapid experimentation, collaboration, and continuous improvement. Our teams work on mission‑critical platforms that anticipate, detect, and resolve issues before they impact patients, providers, or business operations. As a remote‑first, part‑time employer, careerzynith offers flexible work arrangements that respect work‑life balance while delivering high‑impact results on a global scale.
Position Summary
careerzynith is seeking a highly motivated Data Scientist to join our AI‑Ops team on a part‑time, remote basis. In this role you will design, develop, and operationalize advanced AI and statistical models that monitor, predict, and remediate anomalies across massive data‑center environments. You will collaborate closely with senior engineers, product owners, and cross‑functional stakeholders to translate complex business problems into scalable, data‑driven solutions that enhance the reliability, performance, and security of careerzynith’s health‑care platforms.
Key Responsibilities
- Partner with product and engineering teams to define AI‑driven use cases that improve the resilience of the CVS Wellbeing framework.
- Design, train, and validate machine‑learning models (including deep learning, time‑series forecasting, and anomaly detection) using Python, R, and SQL.
- Develop end‑to‑end data pipelines that ingest, cleanse, and transform structured and unstructured data from cloud platforms such as GCP and AWS.
- Implement and maintain production‑grade AI services, ensuring they meet strict SLAs for latency, accuracy, and scalability.
- Conduct rigorous A/B testing, performance benchmarking, and root‑cause analysis to continuously improve model efficacy.
- Document model architecture, data lineage, and operational procedures to support knowledge sharing across the organization.
- Mentor junior data engineers and contribute to a collaborative, knowledge‑rich environment.
- Stay abreast of emerging AI research, tools, and best practices, and proactively propose innovative solutions.
Required Qualifications
- Education: Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
- Experience: Minimum 2 years of hands‑on experience building AI/ML solutions for large‑scale data environments.
- Programming Skills: Proficiency in Python, R, and SQL; familiarity with libraries such as TensorFlow, PyTorch, scikit‑learn, and pandas.
- Data Expertise: Demonstrated ability to work with data extraction, cleaning, feature engineering, and analysis on massive datasets.
- Statistical Modeling: Strong background in statistical inference, predictive modeling, and supervised/unsupervised learning techniques.
- Communication: Excellent verbal and written communication skills; ability to convey complex technical concepts to non‑technical audiences.
- Collaboration: Proven track record of thriving in cross‑functional, collaborative teams and contributing to shared goals.
- Attention to Detail: Meticulous approach to data quality, model validation, and documentation.
Preferred Qualifications
- Master’s or Ph.D. in a quantitative discipline such as Statistics, Machine Learning, or Computer Science.
- Experience with cloud data platforms (e.g., Google Cloud Platform, Amazon Web Services) and big‑data technologies like Spark or Hadoop.
- Hands‑on experience building production‑grade AI pipelines, including CI/CD integration and containerization (Docker, Kubernetes).
- Background in developing AI solutions for IT operations, infrastructure monitoring, or cybersecurity.
- Familiarity with AIOps frameworks and the ability to translate business requirements into AI‑driven automation.
- Demonstrated ability to lead technical discussions, provide expert guidance, and influence strategic direction.
Core Skills & Competencies
- Analytical Thinking: Ability to dissect complex problems, identify root causes, and propose data‑centric solutions.
- Innovation Mindset: Passion for exploring new algorithms, tools, and methodologies to stay ahead of industry trends.
- Project Management: Capability to manage multiple priorities, meet deadlines, and deliver high‑quality outcomes in a part‑time schedule.
- Teamwork: Strong interpersonal skills, openness to feedback, and a commitment to collective success.
- Ethical AI: Understanding of responsible AI practices, data privacy, and compliance considerations in the health‑care sector.
Learning & Development Opportunities
careerzynith invests heavily in the professional growth of its employees. As a Data Scientist on our AI‑Ops team, you will have access to:
- Mentorship from senior AI architects and industry veterans.
- Sponsored certifications (e.g., Google Cloud Professional Data Engineer, AWS Machine Learning Specialty).
- Quarterly internal hackathons focused on emerging AI technologies.
- Conference attendance budgets for events such as NeurIPS, KDD, and Strata Data Conference.
- Dedicated learning time each month to explore new tools, research papers, or side projects.
Culture & Work Environment
careerzynith fosters a high‑velocity, inventive, and cooperative climate where every voice matters. Our remote‑first policy ensures you can work from anywhere in the United States while staying connected through:
- Weekly virtual “coffee chats” to build relationships across teams.
- Collaborative platforms (Slack, Confluence, GitHub) that enable real‑time knowledge sharing.
- Inclusive diversity initiatives that celebrate different perspectives and backgrounds.
- Flexible scheduling that respects personal commitments and promotes work‑life harmony.
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 and sick leave.
- Wellness stipend for home office setup, ergonomic equipment, or fitness programs.
- Employee assistance program (EAP) for mental health support.
- Performance‑based bonuses tied to project milestones and impact.
Career Path & Advancement
Starting as a part‑time Data Scientist at careerzynith opens doors to a variety of future roles, such as:
- Senior Data Scientist – leading larger AI initiatives and strategic roadmaps.
- AI Solutions Architect – designing enterprise‑wide AI platforms.
- Product Lead – shaping the vision for AI‑driven health‑care products.
- Technical Manager – overseeing multidisciplinary teams and driving cross‑functional collaboration.
Our transparent promotion framework ensures that high performers are recognized and rewarded, whether they choose to stay part‑time or transition to a full‑time position.
How to Apply
If you are excited about leveraging AI to safeguard critical health‑care infrastructure and thrive in a flexible, remote environment, we want to hear from you. Please submit your resume, a brief cover letter outlining your relevant experience, and any portfolio or GitHub links that showcase your AI projects.
Join careerzynith today and be part of a mission‑driven team that is redefining the future of health‑tech operations.