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Data Science Engineer Jobs in Connecticut (NOW HIRING)

Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high-value business capabilities * Architect and build ...

Lead data science projects in close collaboration with IT, Data Engineering, Application development, PMO and business leaders to deliver high-value business capabilities * Architect and build ...

Data Engineer

Hartford, CT · On-site

$115K - $138K/yr

Data Engineer - GE08AE We're determined to make a difference and are proud to be an insurance ... Within Customer Operations Data Science, we build modern AI products that optimize customer ...

Data Engineer

Greenwich, CT

$128K - $154K/yr

You will advocate for the thoughtful application of modern data engineering, data science, and AI approaches. Responsibilities * Write productionquality code for data ingestion, transformation ...

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

You will advocate for the thoughtful application of modern data engineering, data science, and AI approaches. Responsibilities * Write productionquality code for data ingestion, transformation ...

... their data science or AI journey. Qualifications Qualifications: 4-7 years of relevant actuarial, technical, or research experience. Strong programming skills, particularly in Python, including ...

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

You will advocate for the thoughtful application of modern data engineering, data science, and AI approaches. Responsibilities * Write production-quality code for data ingestion, transformation ...

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Showing results 1-20

Data Science Engineer information

See Connecticut salary details

$42.3K

$123.4K

$168.9K

How much do data science engineer jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data science engineer in Connecticut is $123,397.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $130,800.00 per year, depending on experience, location, and employer.

What engineers make 500,000?

Senior data science engineers, machine learning engineers, and software engineers with extensive experience and advanced skills in areas like AI, big data, and cloud computing can earn salaries of $500,000 or more, especially in high-cost-of-living regions or within top tech companies. Achieving this level often requires advanced degrees, certifications, and a strong track record of impactful projects.

Is 30 too late for data science?

Data Science Engineers can enter the field at any age, including 30, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to ensure data quality and accessibility.

Is data science high paying?

Data science engineers typically earn high salaries due to their specialized skills in statistical analysis, programming, and machine learning. Salaries vary by experience, location, and industry, but data science roles are generally considered well-compensated within the tech field.
What are popular job titles related to Data Science Engineer jobs in Connecticut? For Data Science Engineer jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Data Science Engineer jobs in Connecticut look for? The top searched job categories for Data Science Engineer jobs in Connecticut are:
Infographic showing various Data Science Engineer job openings in Connecticut as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $123,397 per year, or $59.3 per hour.

Head of Data Science Technology Solutions

Franklintempleton

Stamford, CT

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 10 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.