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Manager Of Data Science Jobs (NOW HIRING)

Job Location - Burbank, CA Type - Contract (3 months) Pay Rate - $67.31 Per Hour (W2 Only) What We Do/Project Seeking a hands-on data scientist to fill the Manager of Data Science position within our ...

Director of Data Science

New York, NY · On-site

$225K - $250K/yr

Managing and growing a team of data scientists focused on modeling key business problems. * Mentoring and guiding team members as they build out quantitative models in python using industry-standard ...

Original Post Date: 4/3/2026 VP of Data Science Kaizen Analytix LLC, an analytics products and ... Through understanding of Agile project management methodology * Ability to travel as dictated by ...

Partner with Analytics, Data Science, Product, Technology, and business stakeholders to translate ... * 2+ years of experience managing or formally leading data engineers. * Strong hands-on ...

Partner with Analytics, Data Science, Product, Technology, and business stakeholders to translate ... * 2+ years of experience managing or formally leading data engineers. * Strong hands-on ...

Ask anyone who knows us - the caliber of our people sets us apart. MANAGER, DATA SCIENCE The Manager of Data Science will build and lead a focused, high-impact team solving complex, high-value ...

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Manager Of Data Science information

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$31K

$97.1K

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How much do manager of data science jobs pay per year?

As of Aug 15, 2026, the average yearly pay for manager of data science in the United States is $97,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,000.00 and $125,500.00 per year, depending on experience, location, and employer.

What is the difference between Manager Of Data Science vs Data Scientist?

AspectManager Of Data ScienceData Scientist
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often leadership experienceBachelor's or Master's in Data Science, Statistics, or related field; strong technical skills
Work EnvironmentOversees teams, manages projects, collaborates with stakeholdersFocuses on data analysis, model development, and technical problem-solving
Employer & Industry UsageUsed in organizations with data teams, analytics departmentsCommonly employed in tech, finance, healthcare, and research sectors

The main difference between a Manager Of Data Science and a Data Scientist is the level of responsibility. Managers oversee teams and strategic initiatives, while Data Scientists focus on technical data analysis and model building. Both roles require strong analytical skills, but the Manager role emphasizes leadership and project management.

How does a manager of data science typically balance hands-on technical work with team leadership responsibilities?

A Manager of Data Science often divides their time between overseeing project execution and supporting their team's professional growth. While they may still participate in high-level technical decision-making and occasionally contribute to code or modeling, much of their focus shifts to setting strategic direction, mentoring team members, and facilitating cross-functional collaboration. They are responsible for ensuring that projects align with business goals, providing technical guidance, and creating an environment where data scientists can thrive. Effective managers also spend time communicating with stakeholders to translate business needs into actionable data projects.

What are the key skills and qualifications needed to thrive as a manager of data science, and why are they important?

To thrive as a Manager of Data Science, you need advanced expertise in data analytics, machine learning, and statistical modeling, typically backed by a degree in a quantitative field and prior experience in data science roles. Familiarity with tools like Python, R, SQL, cloud platforms (e.g., AWS, Azure), and project management systems is essential, and certifications such as Certified Analytics Professional (CAP) can be valuable. Strong leadership, communication, and problem-solving skills help in guiding teams, translating business needs into data solutions, and fostering collaboration. These skills and qualities are crucial for delivering actionable insights, driving innovation, and ensuring successful data-driven strategies in complex organizational environments.

What is a manager of data science?

A Manager of Data Science is a leadership role responsible for overseeing a team of data scientists and analysts, guiding data-driven projects, and ensuring that business objectives are met through data analysis and modeling. They collaborate with stakeholders to identify business needs, design analytical solutions, and manage the end-to-end process of extracting insights from large datasets. In addition to technical expertise, this role requires strong leadership, project management, and communication skills to translate complex findings into actionable strategies.

What cities are hiring for Manager Of Data Science jobs?

Cities with the most Manager Of Data Science job openings:

What are the most commonly searched types of Of Data Science jobs?

The most popular types of Of Data Science jobs are:

Who are the top companies hiring for Manager Of Data Science jobs?

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What states have the most Manager Of Data Science jobs?

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Manager of Data Science

Odesus

Burbank, CA

$67.31/hr

Full-time

Posted 15 days ago


Job description

Job Location - Burbank, CA

Type - Contract (3 months)

Pay Rate - $67.31 Per Hour (W2 Only)

Job Description

What We Do/Project

Seeking a hands-on data scientist to fill the Manager of Data Science position within our Sales organization's Data Science team. Our Data Science team works very closely with Sales and Marketing, and in this position you will maintain and extend existing statistical and machine-learning work that informs how we window, price, and forecast content - including title-level release windowing, price optimization, and demand/revenue forecasting. Working under the direction of the VP of Data Science, you will pick up in-flight models and dashboards and keep them running and accurate. You should be comfortable in a fast-moving environment and able to balance scheduled deliverables with ad-hoc analytical requests.

Job Responsibilities / Typical Day in the Role Data Analysis & Modeling

  • Maintain, validate, and extend existing forecasting, pricing, and windowing models built in Python (pandas, scikit-learn, statsmodels) and SQL against Snowflake.
  • Write clean, reproducible, version-controlled code (Git).
  • Automate recurring data extraction and preparation pipelines to reduce manual effort.
  • Assess model quality with appropriate validation (holdout/backtesting) and error metrics (e.g., MAPE, RMSE, bias), and flag when a model needs retraining or rework.
  • Turn analysis into clear, decision-ready storylines - visual and written - for non-technical audiences. Applying AI & GenAI in the Workflow
  • Use AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate coding, refactoring, and debugging while keeping a human-in-the-loop review of all output.
  • Apply large language models (LLMs) to practical, day-to-day tasks: summarizing datasets and results, drafting documentation, generating and explaining SQL/Python, and accelerating exploratory analysis.
  • Critically evaluate AI output for correctness, and follow enterprise data-privacy, security, and approved-tool guidelines when using AI on data. Visualization & Application Development
  • Build and maintain Tableau dashboards that monitor content, customer, and revenue trends for Sales, Marketing, and other business stakeholders.
  • Develop self-serve interactive tools (Streamlit and/or Tableau) so partner teams can explore results without analyst support.
  • Create views of model diagnostics and archived results so the team can track model performance over time. Collaboration & Mindset
  • Partner day-to-day with Sales and Marketing to understand their questions and deliver clear, useful analysis.
  • Work under the direction of the Director and VP of Data Science, translating their priorities into delivered analyses.
  • Pivot quickly between planned work and urgent ad-hoc requests without losing rigor.
  • A strong communicator and eager learner - open to coaching and to actively growing and strengthening communication skills over the engagement.

Must Have Skills / Requirements 1) Python and SQL coding experience for data manipulation, analysis, and modeling. a. 2+ years 2) Practical experience with core ML/statistics libraries (e.g., scikit-learn, statsmodels, pandas) and standard model-validation techniques. a. 2+ years 3) Experience querying a cloud data warehouse (Snowflake preferred). a. 2+ years 4) Basic working knowledge of Tableau - the team relies on it heavily to deliver insights to Sales and Marketing. a. 2+ years 5) Comfort using and sound judgment about AI-assisted coding tools and LLMs in a professional setting. a. 2+ years 6) Version control with Git and an ability to produce reproducible work. a. 2+ years

Nice to Have Skills / Preferred Requirements 1) Experience in media, entertainment, streaming, or subscription/consumer businesses. 2) Experience supporting Sales and/or Marketing stakeholders. 3) Exposure to forecasting, pricing/elasticity, or windowing/release-strategy analytics. 4) Experience integrating LLM APIs or building simple RAG / natural-language-to-SQL prototypes. 5) Familiarity and/or experience with Streamlit. 6) Master's degree preferred. Fresh out of a master's program is a big plus (also serves as years of experience).

Soft Skills: 1) Good written and verbal communication skills, with an openness to growing and strengthening them, and comfort explaining technical work to non-technical Sales and Marketing partners.

Technology Requirements: 1) Python and SQL coding experience for data manipulation, analysi


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About Odesus

Sourced by ZipRecruiter

Industry

Recruiting and staffing services

Company size

51 - 200 Employees

Headquarters location

Los Angeles, CA, US

Year founded

2001