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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** TekWissen LLC - **Location:** New York, NY, United States (Remote available) - **Experience:** Expert - **Salary:** $87,743.0 - $88,000.0 - **Contract:** Temporary contract - **Skills:** Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Disaster Recovery, Python (Programming Language), Machine Learning, Operational Databases, Cloud Services, SQL Databases, Data Streaming, Workflow Management Systems, Data Logging, Google Cloud, Cloud Platform System, Apache Spark, Kubernetes, Information Technology, Apache Flink, Production Code, Apache Kafka, Spark Streaming, Data Management, Machine Learning Operations, Software Version Control, Data Pipelines, Databricks - **Published:** September 4, 2026 - **Apply:** https://www.careerjet.com/jobad/us60ea2e6b50d5e801f20f149e413c4e4b ## About the Role * Advanced (Master or PhD) degree with specialization in Statistics, Computer Science, Data Science, Economics, Mathematics, Operations Research or another quantitative field or equivalent. * 5+ years of hands-on experience supporting production data, analytics, or machine learning workflows in a complex environment. * Advanced proficiency in Python and SQL, including the ability to read, troubleshoot, and improve unfamiliar production code. * Demonstrated experience building, operating, and troubleshooting scheduled data and model pipelines at scale. * Strong understanding of data dependencies, schema evolution, backfills, idempotent processing, failure recovery, and data-quality controls. * Ability to diagnose issues across multiple systems and drive resolution when ownership is distributed across teams. * Clear written and verbal communication, including concise incident updates, operating documentation, and stakeholder-ready explanations. * Experience with workflow orchestration, version control, automated testing, release practices, and cloud-based data platforms. * Experience supporting machine learning lifecycle workflows, including training, scoring, validation, deployment coordination, and monitoring. * Experience with tools such as Airflow, Databricks, Spark, dbt, Kubernetes, or comparable workflow and data platforms. * Experience with cloud services such as Google Cloud, AWS, or Azure and with large relational or non-relational datasets. * Familiarity with streaming or event-driven data workflows using technologies such as Kafka, Spark Streaming, or Flink. * A proactive operating style that spots risks early, follows issues through closure, and improves the system after recovery. * Strong ownership, sound judgment, and comfort balancing immediate restoration with durable prevention. * A collaborative approach that builds trust with data scientists, platform specialists, data owners, and business partners. * Interest in media, streaming, customer analytics, or large-scale digital products., Job Description ** Please note that due to city requirements only applicants with a master's degree and at least 3 years of related work experience will be considered. In additio… + Just now ## Description * Own the day-to-day health and execution of production model pipelines and the data pipelines that supply them. * Manage recurring refresh schedules, dependencies, handoffs, and delivery commitments across batch and near-real-time workflows. * Monitor pipeline runs, data freshness, model outputs, and downstream availability; identify emerging issues before they affect stakeholders. * Lead triage and resolution when workflows fail or outputs are delayed, coordinating the right data science, platform, data, and business partners through closure. * Diagnose root causes across source data, transformations, runtime environments, orchestration, model execution, and downstream delivery. * Create automated checks for data quality, schema changes, completeness, reasonableness, and model-output validation. * Partner with data scientists to translate notebooks and analytical workflows into repeatable, supportable production processes. * Coordinate releases, model updates, backfills, reruns, and recovery procedures with clear validation and stakeholder communication. * Improve observability through practical logging, alerting, run histories, service expectations, and operational dashboards. * Maintain current documentation for pipeline logic, dependencies, ownership, schedules, recovery steps, and known constraints. * Reduce recurring manual work and operational risk through reusable patterns, automation, and thoughtful workflow simplification. * Communicate pipeline status, incidents, risks, and resolution plans clearly to both technical and nontechnical stakeholders. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Understanding Kubernetes in a visual way](https://www.wearedevelopers.com/videos/100085-understanding-kubernetes-in-a-visual-way) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)