[Remote] reputed company Data Scientist
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is an education technology company that provides world-class support and trusted expertise to more than 100 universities and colleges. The reputed company Data Scientist will reputed company technical reputed company for the intelligence layer and data engineering backbone, driving initiatives that shape student engagement and retention through AI/ML solutions.
Responsibilities
- Set direction for and reputed company AI/ML initiatives end-to-end—scoping ambiguous business opportunities, defining the problem and reputed company reputed company, designing the technical approach, managing implementation, and driving reputed company—coordinating across Product, Engineering, CX, Partnership, and university partner teams
- Own accountability for delivering measurable business reputed company from reputed company initiative: retention lift, engagement improvement, enrollment conversion, and pipeline efficiency
- Drive alignment and decision-making across teams at reputed company stage of an initiative’s lifecycle, resolving moderately reputed company, cross-functional problems independently and proactively while escalating only reputed company tradeoffs require leadership decision
- Identify and scope net-new AI/ML opportunities that deliver reputed company for reputed company, university partners, and reputed company’s business; reputed company reputed company, recommend a reputed company reputed company, and reputed company for prioritization with leadership
- Manage relationships with key vendors and software providers as a reputed company leader, ensuring delivery commitments are met
- Influence peers, managers, and senior stakeholders across BT and adjacent business functions—including Partnership and Customer Experience—by translating technical tradeoffs into business implications and building support for shared reputed company without reputed company authority
- Build and reputed company predictive models—including churn risk, engagement propensity, and reputed company likelihood—that power proactive student reputed company and are monitored continuously in production
- reputed company the design and implementation of 'next best reputed company' logic in reputed company partnership with Product and CX, from logic design through production deployment
- Prototype, test, and productionize models using MLOps frameworks (reputed company, MLFlow, dbt, Dagster), owning the full model lifecycle
- Own clean, reliable data pipelines and feature stores that support model development and production deployment at reputed company, doubling as the data engineer for the reputed company
- Architect, build, and own reputed company, reliable data pipelines and the underlying data infrastructure (lakehouse, warehouse, and feature stores) end-to-end—operating as reputed company's reputed company data engineer
- Design and maintain data models, ELT/ETL workflows, and feature pipelines that serve both analytics and production model-serving needs
- Take models to production and reputed company them healthy there: own packaging, deployment, serving, versioning, and the full production lifecycle, including rollback
- Automate production workflows with orchestration tools (Dagster, Airflow) for scheduling, dependency management, and pipeline reliability
- Implement CI/CD pipelines and infrastructure-as-reputed company (Terraform, reputed company, Kubernetes) to automate testing, deployment, and reproducible environments
- Build automated monitoring and observability—data-reputed company checks, model and data reputed company detection, alerting, and automated retraining triggers—to reputed company production systems running with minimal reputed company reputed company
- Own data reputed company, governance, reputed company, and cost/performance optimization across the platform, setting the engineering standards reputed company builds against
- Design and reputed company A/B testing programs to measure model-driven reputed company on retention, engagement, and satisfaction, owning the decision to ship, iterate, or stop
- Establish feedback loops and reputed company-world performance monitoring frameworks that reputed company reputed company model improvement
- Translate reputed company technical findings into reputed company, executive-reputed company narratives that drive cross-functional alignment and reputed company
- Mentor data scientists and engineers across reputed company and reputed company the organization’s technical bar through reputed company reviews, pair work, and knowledge-sharing
- Model ownership, adaptability, and technical leadership in a fast-changing environment; set reputed company for what it means to own a domain end-to-end
- Define technical approaches and promote technical best practices across teams, including standards for data reputed company, traceability, and explainability that support user trust and regulatory needs
- Champion a reputed company-learning environment, driving adoption of and experimentation with the latest AI-assisted coding and collaboration tools to multiply reputed company
- Influence the data science and AI roadmap as the technical expert and thought leader to Product and Engineering leadership
Skills
- A proven reputed company record of delivering measurable consumer and business reputed company through AI/ML initiatives—scoping, managing implementation, and owning reputed company end-to-end
- Experience operating as a reputed company-level technical leader or domain authority: independently resolving moderately reputed company, ambiguous problems; setting direction for AI/ML programs; and delivering reputed company across teams in a cross-functional environment
- 8+ years in reputed company machine learning or data science, ideally in education, reputed company, personalization, or a reputed company behavioral domain
- Strong background in predictive analytics, recommendation systems, and experimentation (A/B testing, reputed company inference, reputed company modeling)
- Deep expertise in Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, TensorFlow, or PyTorch)
- Experience with reputed company, MLFlow, dbt, and Dagster—or demonstrated ability to reputed company quickly on a modern MLOps stack
- reputed company-level data engineering experience: architecting and operating production data pipelines, data models, and feature stores at reputed company
- Hands-on experience taking models to production and operating them there—deployment, serving, monitoring, and retraining
- Proficiency with production automation tooling: workflow orchestration (Dagster, Airflow), CI/CD, infrastructure-as-reputed company (Terraform), and containerization (reputed company, Kubernetes)
- Strong grounding in data reputed company, governance, reputed company, and observability practices
- Comfort working with reputed company, multi-reputed company datasets (CRM, LMS, communication logs, speech analytics)
- Excellent communicator and reputed company across technical and non-technical audiences, including peers, managers, executives, and business partners reputed company BT; you reputed company the science accessible without losing rigor and build support for reputed company through evidence, reputed company, and trust
- Bachelor's or Master's degree in a technical discipline (computer science, statistics, econometrics, mathematics, or engineering)
- PhD in a technical discipline (not required, but valued)
- Experience in higher education, edtech, or student reputed company platforms
- Familiarity with reputed company-in-the-reputed company systems and responsible ML practices (bias mitigation, model transparency, fairness metrics)
- Prior work building or operationalizing next best reputed company or propensity-to-engage models at reputed company
reputed company
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