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Overnight Python Data Science Jobs (NOW HIRING)

A well-established energy trading firm in Houston is seeking a seasoned Python Data Engineer to ... Interface directly with traders, analysts, researchers, and data scientists to gather, refine, and ...

Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes * Perform ...

Data Science - 7+ yrs * SAS - 5+ * Python -5+ * SQL * Jupyter, Data Robot preferred * AI tools preferred * BS w/financial svcs or auto industry exp. required Required: • Bachelor's degree (Major in ...

Contribute to our developer tools and Python ETL toolkit, including standardization and ... Computer Science, MIS or related degree * Experience with Data Engineering and building data ...

Contribute to our developer tools and Python ETL toolkit, including standardization and ... Computer Science, MIS or related degree * Experience with Data Engineering and building data ...

Python data science skills for data manipulation, web frameworks, visualization, and Machine Learning. * Develop and deploy imaging data collection and analysis monitoring database and build Web Apps ...

Design develop and deploy machine learning models and algorithms using Python Lead data science projects from concept to implementation ensuring timely delivery and quality outcomes * Perform ...

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How much do overnight python data science jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for overnight python data science in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What are Overnight Python Data Science jobs?

Overnight Python Data Science jobs involve working night shifts to perform data analysis, build models, or process data using Python programming. These roles may include tasks like cleaning datasets, running automated pipelines, and generating reports for teams that operate on a 24-hour cycle. Such positions are common in industries that require round-the-clock data monitoring or support, such as finance, healthcare, or IT operations. Professionals in these roles typically have experience with Python, data science libraries, and may collaborate with global teams across different time zones.

What are the main challenges of working as an Overnight Python Data Science professional, and how can I succeed in this role?

Working as an Overnight Python Data Science professional often means handling data pipelines, model monitoring, and urgent troubleshooting during hours with limited team support. The main challenges include quickly resolving unexpected data issues, maintaining high attention to detail during late hours, and communicating findings to daytime teams. Success in this role relies on strong problem-solving skills, proactive communication (such as clear shift handovers), and the ability to work independently while following established protocols. Building robust documentation and automating regular tasks can also help manage workload and reduce errors.

What are the key skills and qualifications needed to thrive as an Overnight Python Data Science professional, and why are they important?

To thrive as an Overnight Python Data Science professional, you need strong analytical skills, proficiency in Python programming, and a solid understanding of statistics and machine learning concepts, often backed by a degree in a quantitative field. Familiarity with tools such as Jupyter Notebook, Pandas, Scikit-learn, and data visualization libraries, along with experience using databases and cloud platforms, is typically required. Excellent problem-solving skills, attention to detail, and the ability to work independently during non-standard hours help you excel in this role. These skills and qualities are vital for efficiently analyzing data, building reliable models, and delivering actionable insights in a time-sensitive, often autonomous overnight environment.

What is the difference between Overnight Python Data Science vs Data Analyst?

AspectOvernight Python Data ScienceData Analyst
Required SkillsPython, data analysis, machine learning, statistical modelingExcel, SQL, data visualization, basic statistics
Work EnvironmentRemote or night shifts, tech-focused companies, data-driven rolesOffice-based or remote, business or marketing departments
Industry UsageTech, finance, e-commerce, healthcareRetail, finance, marketing, consulting

Overnight Python Data Science roles focus on advanced data analysis, machine learning, and programming skills, often requiring night shifts and remote work. Data Analysts typically handle data visualization, reporting, and basic analysis during regular hours. Both roles are essential in data-driven industries but differ in technical complexity and work schedules.

What cities are hiring for Overnight Python Data Science jobs? Cities with the most Overnight Python Data Science job openings:
What are the most commonly searched types of Python Data Science jobs? The most popular types of Python Data Science jobs are:
What states have the most Overnight Python Data Science jobs? States with the most job openings for Overnight Python Data Science jobs include:

Python Data Scientist / Data Engineer

HRC Global Services

Virginia Beach, VA • Remote

Full-time

Posted 19 days ago


Job description

Python Data Scientist / Data Engineer

Python Data Scientist / Data Engineer (PySpark, ETL, Notebooks, Databricks) Summary We're hiring a versatile Python Data Scientist / Data Engineer to design, implement, and productionize scalable data pipelines and analytics workflows.

The role requires deep PySpark experience, strong ETL design, experience with interactive notebooks, and familiarity with Databricks or similar managed Spark platforms.

Key responsibilities

* Design and build robust ETL/ELT pipelines using PySpark for batch and near-real-time workflows.

* Develop, optimize, and schedule Spark jobs on Databricks (or equivalent Spark environment).

* Work with data scientists and product teams to transform business requirements into data models, features, and dashboards.

* Implement data validation, monitoring, and lineage to ensure data quality and reliability.

* Create reproducible notebooks for exploration, prototyping, and handoff to production pipelines.

* Tune performance of Spark jobs (memory, partitioning, shuffle reduction) and optimize cluster usage.

* Collaborate on building CI/CD for data workflows, including tests for data transformations and schema changes.

* Document architecture, ETL processes, and best practices.

Required qualifications

* 3+ years experience in data engineering, data science, or analytics engineering roles.

* Strong Python programming and hands-n PySpark experience developing data transformations at scale.

* Experience with Databricks (jobs, clusters, Delta Lake) or equivalent managed Spark platforms.

* Solid understanding of ETL/ELT patterns, data modeling, and data warehousing concepts.

* Comfortable using Jupyter or Databricks notebooks for exploration and prototyping.

* Experience with SQL and working knowledge of cloud data storage systems (S3, ADLS) and databases.

* Familiarity with orchestration tools (Airflow, Prefect, Dagster) and awareness of CI/CD for data pipelines.