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Manager Of Data Science Jobs (NOW HIRING)

Be part of something groundbreaking At AIG, we are making long-term investments in a brand-new ... How you will create impact As a Manager of Data Science at AIG, you will play a critical role in ...

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities ...

Senior Manager, Data Science We are Lennar Lennar is one of the nation's leading homebuilders, dedicated to making an impact and creating an extraordinary experience for their Homeowners, Communities ...

We are tackling one of the world's most important infrastructure challenges: helping the energy ... As a Data Science Manager, you will act as a pivotal technical leader to bridge the gap between ...

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Manager Of Data Science information

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$31K

$97.1K

$172K

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

As of Jul 6, 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 does a data scientist manager do?

A data scientist manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often utilizing tools like Python, R, or SQL, and may require leadership and communication skills alongside technical expertise.

How much do data scientist managers make?

Data science manager salaries typically range from $110,000 to $180,000 annually, depending on experience, location, and company size. Senior managers or those in high-demand industries can earn over $200,000, often with additional bonuses and stock options.

What is the 80 20 rule in data science?

The 80/20 rule, also known as Pareto principle, suggests that roughly 80% of effects come from 20% of causes. In data science, it often means focusing on the most impactful features or data points to improve model performance efficiently.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Director of Data Science, Chief Data Officer, or Lead Data Scientist, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 with bonuses and stock options. These roles typically require extensive experience, advanced skills in machine learning, big data tools, and leadership abilities.
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:
What states have the most Manager Of Data Science jobs? States with the most job openings for Manager Of Data Science jobs include:

Head of Data Science Technology Solutions

Franklintempleton

Baltimore, MD

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 28 days ago


Job description

At Franklin Templeton, we're advancing our industry forward by developing new and innovative ways to help our clients achieve their investment goals. Our dynamic firm spans asset management, wealth management, and fintech, offering many ways to help investors make progress toward their goals. Our talented teams working around the globe bring expertise that's both broad and unique. From our welcoming, inclusive, and flexible culture to our global and diverse business, we provide opportunities to help you reach your potential while helping our clients reach theirs.

Come join us in delivering better outcomes for our clients around the world!

The Head of Data Science will lead the development of a globally scalable, AI-enabled data science capability within Investment Technology Solutions (ITS), delivering advanced analytics and machine learning solutions that directly enhance investment outcomes across asset classes.

Reporting to the Head of ITS, this role will bridge front-office investment teams and enterprise technology-ensuring that data science capabilities are platform-based, industrialized, and embedded into portfolio construction, risk management, and investment operations workflows.

The mandate combines three core objectives:

Deliver measurable impact to investment performance and risk management. Build and scale an enterprise-grade data science and AI platform. Establish a globally collaborative operating model aligned to ITS strategy.

Key Responsibilities

Investment-Focused Delivery

  • Partner closely with CIOs, Portfolio Managers, and Research Heads to translate investment challenges into scalable analytical solutions.

  • Develop and productionalize alpha signals, risk models, optimization engines, liquidity analytics, and scenario modelling capabilities.

  • Ensure analytics are embedded within portfolio construction, trading, and risk systems (e.g., Aladdin, Wall Street Office, Axioma or equivalent platforms).

  • Drive quantifiable improvements in performance attribution, risk-adjusted returns, drawdown management, and portfolio efficiency.

Data Science Platform & Architecture

  • Design and implement a robust, cloud-enabled data science platform supporting:

    • Research and experimentation environments

    • Feature stores and reusable signal libraries

    • Model development, validation, and testing frameworks

    • MLOps and model lifecycle management

    • Deployment pipelines into investment and risk platforms

  • Ensure architecture supports cross-asset reuse, security, auditability, and regulatory compliance.

  • Align platform standards with broader ITS data and infrastructure strategy.

Enterprise & Cross-Functional AI Enablement

  • Collaborate with Risk, Finance, Operations, and Distribution teams to extend AI capabilities where aligned to investment technology priorities.

  • Contribute to enterprise AI initiatives including stress testing automation, operational intelligence, and advanced reporting analytics.

  • Represent ITS Data Science in enterprise AI governance and model risk forums.

  • Promote responsible AI principles including explainability, transparency, and bias mitigation.

Organizational Build & Global Scale

  • Establish and scale a high-performing global data science organization embedded within ITS.

  • Develop a federated delivery model supporting regional investment teams across market hours.

  • Create clear differentiation between quantitative research, data science, AI engineering, and ML platform engineering roles.

  • Implement strong talent development pathways to build deep capital markets and vendor platform expertise.

Product Mindset & Value Realization

  • Operate data science as a product capability, with defined roadmaps, prioritization frameworks, and measurable value tracking.

  • Establish adoption metrics and performance KPIs for all deployed solutions.

  • Balance near-term market support needs with longer-term platform innovation.

Governance & Controls

  • Implement robust model validation, monitoring, and lifecycle management processes.

  • Ensure compliance with model risk management standards and regulatory expectations.

  • Maintain data lineage transparency and documentation standards aligned with ITS governance frameworks.

Candidate Profile

Experience

  • 10+ years' experience in asset management, capital markets, or quantitative investment technology environments.

  • Demonstrated leadership building and scaling data science or quantitative analytics teams within a technology-enabled operating model.

  • Proven track record delivering production-grade AI/ML solutions embedded in investment platforms.

  • Experience operating in regulated financial services environments.

Capital Markets Expertise

  • Deep understanding of:

    • Multi-asset portfolio construction and optimization

    • Risk modelling and stress testing

    • Market structure, liquidity dynamics, and execution considerations

  • CFA designation strongly preferred.

  • Advanced degree (PhD/MSc) in quantitative finance, statistics, mathematics, computer science, or related discipline desirable.

Technical & Platform Expertise

  • Strong command of statistical modelling, machine learning, and time-series analysis.

  • Experience integrating alternative datasets into investment workflows.

  • Familiarity with cloud-native data architectures, distributed compute, and MLOps frameworks.

  • Experience working with enterprise investment platforms (e.g., Aladdin, Wall Street Office, Axioma) strongly preferred.

Leadership & Operating Style

  • Technology-forward leader with strong investment credibility.

  • Product-oriented and outcome-driven.

  • Comfortable operating in a global, matrixed ITS organization.

  • Strong communicator capable of influencing senior investment and technology stakeholders.

Franklin Templeton offers employees a competitive and valuable range of total rewards-monetary and non-monetary - designed to support their well-being and recognize their time, talents, and results. Along with base compensation, employees are eligible for an annual discretionary bonus, a 401(k) plan with a generous match, and recognition rewards. We also offer a comprehensive benefits package, which includes a range of competitive healthcare options, insurance, and disability benefits, employee stock investment program, learning resources, career development programs, reimbursement for certain education expenses, paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational wellbeing program. We expect the annual salary for this position to range between $208,000 - $270,000, depending on location and level of relevant experience, plus discretionary bonus.

#EXECUTIVE

#LI-Hybrid

Experience our welcoming culture and reach your professional and personal potential!

Our culture is shaped by the variety of perspectives and experiences brought by talent from around the world. Regardless of your interests, lifestyle, or background, there's a place for you at Franklin Templeton. We provide employees with the tools, resources, and learning opportunities to help them excel in their career and personal life.

By joining us, you will become part of a culture that focuses on employee well-being and provides multidimensional support for a positive and healthy lifestyle. We understand that benefits are at the core of employee well-being and may vary depending on individual needs. Whether you need support for maintaining your physical and mental health, saving for life's adventures, taking care of your family members, or making a positive impact in your community, we aim to have your needs covered. Learn more about the wide range of benefits we offer at Franklin Templeton.

Highlights of our benefits include:

  • Three weeks paid time off the first year

  • Medical, dental and vision insurance

  • 401(k) Retirement Plan with 85% company match on your pre-tax and/or Roth contributions, up to the IRS limits

  • Employee Stock Investment Program

  • Tuition Assistance Program

  • Purchase of company funds with no sales charge

  • Onsite fitness center and recreation center*

  • Onsite cafeteria*

*Only applicable at certain locations

Learn more about the wide range of benefits we offer at Franklin Templeton

Franklin Templeton is an Affirmative Action Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.
If you believe that you need an accommodation or adjustment to search for or apply for one of our positions, please send an email to accommodations@franklintempleton.com. In your email, please include the accommodation or adjustment you are requesting, the job title, and the job number you are applying for. It may take up to three business days to receive a response to your request. Please note that only accommodation requests will receive a response.