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Overnight Data Science Mentor Jobs (NOW HIRING)

You will build, mentor, and lead a high-performing team of data scientists to deliver operational excellence, accelerate product advancement, and drive business value. In this role, you will deeply ...

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Mentor and coach team members while fostering a culture of scientific rigor, collaboration ...

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Mentor and coach team members while fostering a culture of scientific rigor, collaboration ...

Manager Data Science

Philadelphia, PA · On-site

$115K - $192K/yr

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Mentor and coach team members while fostering a culture of scientific rigor, collaboration ...

At Elsevier, data science leadership is about far more than managing projects, models, or roadmaps ... Mentor and coach team members while fostering a culture of scientific rigor, collaboration ...

Director, Data Science

Bellevue, WA · On-site

$156K - $312K/yr

Lead, mentor and grow a team of data scientists, ML engineers and data analysts dedicated to Marketplace initiatives across seller lifecycle. * Partner with product, engineering, merchandising, and ...

Data Science Expert

$120 - $170/hr

Experience reviewing technical work or mentoring analytical teams is a plus. Application Process ... Apply your professional data science expertise to high-impact AI evaluation projects. * Work ...

Responsibilities : • Lead and mentor a team of data scientists on performance, growth, production, and day-to-day responsibilities • Partner across business and technology organizations to align ...

Mentor and Guide: Lead and mentor a team of data scientists, fostering a data-driven culture and promoting continuous learning in RPA and AI. * Communicate Effectively: Present findings and ...

OR · On-site

Passion for mentoring senior and junior data scientists, fostering technical excellence, and building a culture of experimentation and rigorous thinking. * Customer Empathy * Experience engaging ...

Director- Data Science

Bellevue, WA · On-site

$156K - $312K/yr

Lead, mentor and grow a team of data scientists, ML engineers and data analysts dedicated to Marketplace initiatives across seller lifecycle. * Partner with product, engineering, merchandising, and ...

Mentorship & Training: You will receive guidance from experienced data scientists and engineers. Expect one-on-one mentorship, regular feedback, and access to learning resources to accelerate your ...

Showing results 21-40

Overnight Data Science Mentor information

What are the key skills and qualifications needed to thrive as an overnight data science mentor, and why are they important?

To thrive as an Overnight Data Science Mentor, you need a solid background in statistics, programming (such as Python or R), and practical experience applying data science methodologies, often supported by a relevant degree or certifications. Familiarity with tools like Jupyter Notebook, SQL, data visualization platforms, and cloud-based collaboration systems is essential. Strong communication, patience, and the ability to explain complex concepts clearly are vital soft skills for guiding learners remotely. These skills ensure effective mentorship, foster student growth, and help maintain a supportive learning environment during overnight hours.

What are the typical responsibilities and challenges faced by an overnight data science mentor?

As an Overnight Data Science Mentor, you are primarily responsible for providing guidance, feedback, and support to data science students outside of regular business hours. This often involves answering technical questions, reviewing project work, and helping learners troubleshoot coding issues in real time. A common challenge in this role is balancing prompt, clear communication with students across different time zones while ensuring complex concepts are explained in an accessible manner. Additionally, working overnight hours requires strong time management and self-motivation. The role is highly collaborative, as you often coordinate with other mentors and instructional staff to ensure consistent support and learning outcomes.

What is the difference between Overnight Data Science Mentor vs Data Scientist?

AspectOvernight Data Science MentorData Scientist
CredentialsTypically requires a background in data science, mentoring experience, and relevant certificationsRequires a degree in data science, statistics, or related fields; certifications are common
Work EnvironmentOften remote, flexible hours, focused on mentoring and trainingUsually office-based or remote, involved in data analysis, modeling, and research
Employer & IndustryEducational platforms, online training companies, startupsTech companies, finance, healthcare, consulting firms
Search & Comparison IntentPeople looking for mentorship roles or part-time mentoring opportunitiesIndividuals seeking full-time data analysis or modeling roles

The main difference is that an Overnight Data Science Mentor focuses on guiding and training learners, often remotely and part-time, while a Data Scientist is involved in analyzing data, building models, and making data-driven decisions in a full-time professional setting.

What does an overnight data science mentor do?

An Overnight Data Science Mentor provides guidance and support to students or professionals learning data science, typically during nighttime or off-peak hours. Their main responsibilities include answering questions, reviewing code and projects, offering feedback, and assisting with problem-solving in areas like statistics, machine learning, and programming. This role is especially important for learners in different time zones or those with non-traditional schedules, ensuring continuous support and engagement. Mentors often work remotely and may collaborate with educational platforms or bootcamps to help learners achieve their goals.
What cities are hiring for Overnight Data Science Mentor jobs? Cities with the most Overnight Data Science Mentor job openings:
What are the most commonly searched types of Data Science Mentor jobs? The most popular types of Data Science Mentor jobs are:
What states have the most Overnight Data Science Mentor jobs? States with the most job openings for Overnight Data Science Mentor jobs include:
Infographic showing various Overnight Data Science Mentor job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Data Science Manager

Tapestry

Mountain View, CA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 14 days ago


Tapestry Inc. rating

8.0

Company rating: 8.0 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

1st of 104 rated fashion retailers


Job description

About Tapestry

Tapestry is a team within Alphabet working to build the AI-powered electric grid. We are tackling one of the world's most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.

Originally born at X, Alphabet's moonshot factory, Tapestry brings together experts in energy, AI, software, engineering, and product to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.

This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.

Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.

About the role:

At Tapestry, data drives all our decision-making. Data Scientists work across the organization to help shape our business and technical strategies by processing, analyzing, and interpreting massive datasets. They lead our metrics assessment, analyze massive datasets and derive early insights, and partner with cross functional teams on the right datasets for maximum downstream impact. As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between complex business questions and advanced technical execution. You will build, mentor, and lead a high-performing team of data scientists to deliver operational excellence, accelerate product advancement, and drive business value.

In this role, you will deeply immerse yourself with the team of data scientists in data collection and analysis, develop compelling, synthesized recommendations for senior leadership, and be involved  to help drive implementation. Ultimately, your team's solutions will fundamentally improve electric grid visibility and resilience.

How you will contribute to the team...

1. Team Leadership and Strategic Delivery

  • People Management: Recruit, mentor, and lead a world-class team of data scientists. Cultivate talent through active technical mentorship and clear career development paths.
  • Cross-Functional Alignment: Collaborate with engineering, product, power system experts, and external partners to translate high-level business goals into rigorous data science roadmaps.
  • Executive Communication: Persuasively communicate your team's findings and strategic recommendations to senior executives and cross functional teams, tracking the long-term business impact of the solutions.

2. Data Integrity and Curation Strategy at Scale

  • Pipeline Oversight: Guide the team in discovering, investigating, and deriving insights from large and complex input datasets, both current and potential, from partners and other sources.
  • Gatekeeping Metrics: Oversee the definition of problem framing, test datasets, and core business, product and performance metrics that machine learning models will aim to optimize for.
  • Multi-Stage Quality Control: Ensure data integrity across the pipeline by establishing frameworks to assess intermediate datasets and metrics within multi-stage machine learning processes.
  • Annotation Rigor: Drive a comprehensive and scalable data annotation strategy that prioritizes quality through statistical rigor, ensuring data reliability for all downstream modeling.

3. Problem Definition and Advanced Analytics

  • Grid Visibility and Innovation: Lead the proactive exploration of new problem spaces to fundamentally improve electric grid visibility and resilience.
  • Experimentation Frameworks: Standardize how the team designs, executes, and analyzes A/B tests and other experiments to validate hypotheses and measure product impact.
  • Engineering Best Practices: Champion modern data science workflows, including the application of GenAI techniques for data analysis, ensuring the team follows robust engineering best practices.
What you should have...
  • PhD or Master's in a quantitative field and 8+ years of tech or energy industry work experience as a statistician, quantitative analyst, or data scientist. 
  • 5+ years of experience directly managing or leading high-performing data science and analytics teams, with a proven track record of delivering production-grade data solutions.
  • A proven track record of identifying where data science can add unique value during early product development, alongside a strong ability to influence other teams to collaborate on critical data science work.
  • Advanced skills in experimental design, including the ability to architect, guide, and validate robust A/B testing methodologies and statistical experiments in ambiguous environments.
  • Experience in Python, SQL, R, Pandas, Scikit-Learn, other ML frameworks as appropriate.
  • Experience with electric power grid data, and physics based understanding of electrical networks and utility data. Ability to bridge the gap between power systems and machine learning.
  • Experience in multivariate analysis, stochastic models, and sampling methods. Able to select the right statistical tool to solve for bias, variance, and data drift.
  • Applied experience with building comprehensive machine learning model evaluation tooling and processes on large datasets.
  • Proven ability to "zoom out" from complex technical details to build a cohesive product strategy, and "zoom in" to unblock technical hurdles.
  • Demonstrate strong collaboration with software engineering and cross functional teams to build ML-powered systems ready for production.
  • Exceptional storytelling abilities, with a knack for turning complex data pipelines and model metrics into clear business value for non-technical stakeholders.
Would be great to have...
  • Ability to thrive in ambiguity, set own goals and effectively delivering to them in a very fast-changing environment
  • Attention to detail, project management, and organizational skills
  • Fast learner with capacity to learn about a wide-spread of different technologies and industries
  • Passion for the energy and climate space
  • Track record of delivering scalable solutions to complex software problems
  • Experience in startup or high-growth environments

Tapestry Values:

  • Take charge: We take initiative and own outcomes that move the mission forward.
  • Transform with purpose: We build solutions that solve real problems and create meaningful impact.
  • Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
  • Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
  • Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.

What we offer:

A culture that supports growth, ownership, and meaningful impact, along with...

  • Competitive salary and equity
  • Medical, dental, and vision coverage
  • Generous PTO and flexible hybrid work model
  • 401(k) with employer contribution
  • Professional development
  • The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $207,000 - $304,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.


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