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Top Data Science Jobs (NOW HIRING)

Create career development pathways that attract and retain top data science talent * Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring Advanced Analytics & ML ...

As the new leader of this department it is imperative that you bring disruptive ideas, creative mindsets and hire top-notch technical talent. The head of this new Data Science division will be ...

Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering ... top talent.Elements of the Total Rewards package include competitive base pay and variable ...

EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a ... We are currently seeking a Data Science Manager to lead the development and deployment of advanced ...

New

Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering ... top talent. Elements of the Total Rewards package include competitive base pay and variable ...

Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering ... top talent.Elements of the Total Rewards package include competitive base pay and variable ...

Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering ... top talent.Elements of the Total Rewards package include competitive base pay and variable ...

Bachelor's degree in computer science, Machine Learning, Applied Mathematics, Computer Engineering ... top talent.Elements of the Total Rewards package include competitive base pay and variable ...

Build and develop talent: recruit top-tier data science professionals, design career development frameworks, and create pathways for growth at all levels * Champion the adoption of GenAI, Agentic AI ...

The Data Science Manager is responsible for leading a team of data scientists (individual ... Attract, retain and develop top talent to build an effective and high performing team; Support team ...

Work with confidence knowing your ideas are heard and backed by one of the world's top professional ... KPMG is currently seeking a Manager, Data Science to join our Consulting practice. Responsibilities:

Manager of Data Science

Boulder, CO · On-site

$160K - $215K/yr

... top-tier engineers, data scientists, and privacy experts If you are a curious and analytical data scientist eager to work with privacy-first healthcare data, we'd love to hear from you.

The Data Science team, a part of the broader StubHub Data organization, is looking for an ... Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact

The Data Science team, a part of the broader StubHub Data organization, is looking for an ... Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact

Manager, Data Science

Chicago, IL

$136.16K - $204.24K/yr

OverviewThe Data Science Manager II will lead a team focused on delivering business insights using ... top talent. Actual compensation offered to a candidate may vary based on their unique ...

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Showing results 1-20

Top Data Science information

See salary details

$37.5K

$122.7K

$196.5K

How much do top data science jobs pay per year?

As of May 29, 2026, the average yearly pay for top data science in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Top Data Scientist, and why are they important?

To thrive as a Top Data Scientist, you need advanced proficiency in statistics, machine learning, and programming (commonly in Python or R), typically supported by a degree in computer science, mathematics, or a related field. Familiarity with data analysis tools like Pandas, NumPy, TensorFlow, and data visualization platforms, as well as experience with big data infrastructure such as Hadoop or Spark, is essential. Strong problem-solving ability, critical thinking, and effective communication skills distinguish top performers in this field. These skills and qualities are crucial for extracting actionable insights from complex datasets and driving data-driven decision-making in organizations.

What are some typical challenges a data scientist faces when working on cross-functional teams?

Data scientists often collaborate with professionals from engineering, product management, and business units, which can present challenges such as aligning on project goals, communicating complex technical findings to non-technical stakeholders, and managing differing priorities. It’s common to navigate ambiguity in data requirements or business objectives, requiring strong communication and adaptability. Building successful partnerships across functions is key to ensuring that data-driven insights are actionable and impactful.

What is a data scientist?

A data scientist is a professional who analyzes and interprets complex digital data to help organizations make informed decisions. They use techniques from statistics, computer science, and machine learning to extract insights from large datasets. Data scientists often build predictive models, visualize data trends, and communicate findings to stakeholders. Their work helps businesses optimize operations, identify new opportunities, and solve challenging problems using data-driven approaches.

What is the difference between Top Data Science vs Data Analyst?

AspectTop Data ScienceData Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; often includes certifications in machine learning or AIBachelor's in Statistics, Mathematics, or related fields; certifications in data analysis tools are common
Work EnvironmentResearch and development teams, data science departments, often in tech or finance industriesBusiness units, marketing, finance, or operations teams across various industries
Employer & Industry UsageTech companies, finance, healthcare, e-commerce, and startups focusing on predictive modeling and AIRetail, finance, healthcare, and other sectors focusing on reporting and data interpretation

Top Data Science roles focus on advanced analytics, machine learning, and predictive modeling, requiring specialized skills and higher-level credentials. Data Analysts primarily handle data reporting, visualization, and basic analysis. While both roles work with data, Top Data Science positions involve more complex modeling and algorithm development, often in tech-driven environments.

More about Top Data Science jobs
What states have the most Top Data Science jobs? States with the most job openings for Top Data Science jobs include:
Infographic showing various Top Data Science job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.
Senior Manager, Data Science/ML

Senior Manager, Data Science/ML

CookUnity

New York, NY

Other

Medical, Vision, Retirement, PTO

Posted 16 days ago


Job description

The role:

We're looking for a Senior Manager, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics-you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale.

As Senior Manager, you'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution.

Responsibilities:Strategic Vision & Product Partnership
  • Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes
  • Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities
  • Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems
  • Translate complex product challenges into clear data science problems with measurable success criteria
  • Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration
  • Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.
Team Leadership & Development
  • Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems
  • Foster a culture of innovation, experimentation, and continuous learning within the data science organization
  • Create career development pathways that attract and retain top data science talent
  • Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring
Advanced Analytics & ML Capabilities
  • Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey
  • Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning
  • Develop causal inference methodologies to understand true incrementality of product changes.
  • Ensure models are observable, explainable where needed, and continuously improved post-launch
Product Measurement & Impact
  • Define product success metrics and measurement frameworks that align with business objectives
  • Build scalable dashboards and monitoring systems that provide real-time visibility into product performance
  • Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimization

Qualifications:
  • 8+ years of experience in data science, with at least 3 years in leadership roles managing data scientists or ML engineers
  • Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling
  • Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor
  • Strong product sense and business acumen-ability to identify high-impact opportunities and translate them into data science initiatives
  • Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical
  • Excellent communication skills-ability to explain complex technical concepts to non-technical stakeholders and influence product strategy
  • Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow)
  • Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)
Preferred requirements:
  • PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
  • Experience with real-time ML systems and feature stores
  • Background in recommendation systems or two-tower/multi-modal embeddings
  • Familiarity with generative AI and LLM applications in product contexts
  • Experience building data science teams from scratch or through periods of rapid growth
  • Prior work in subscription businesses or retention-focused products
  • Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)
What Success Looks Like
  • 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership
  • 12 months: Scaled the product data science function with key hires; delivered measurable improvements in personalization and customer engagement metrics; implemented robust experimentation frameworks used across product teams

Learn More About CookUnity

We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles - The values and behaviors that guide how we operate, collaborate, and scale.

We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect!


Benefits

  Health Insurance coverage

 401k Plan

 We grow, you grow: Stock Options Plan granted on Day 1

 Eligible for a bi-annual performance bonus

 Unlimited PTO

 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

 Paid Family leave

 Compassionate Leave: 3-5 days each time the need arises

 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

Wellness perks: access to fitness subsidies to build a healthy lifestyle

AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.

 Personalized Spanish coach

 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!