Head of Data Science & AI
Janus Henderson Global Investors, Chicago, IL, United States
Your opportunity
Position Overview
The Head of Data Science & AI spearheads the asset management firm’s data‑driven initiatives, responsible for developing and executing a strategy to harness data and artificial intelligence across the organization. This role oversees advanced analytics, AI model development, and the governance of AI/ML usage, ensuring that the firm leverages AI ethically and effectively to gain insights—improving investment research, client experiences, and operations. It combines deep technical expertise with leadership and industry knowledge to transform data into a competitive advantage while upholding the strict standards of accuracy, transparency, and client trust expected in asset management.
Key Responsibilities
AI Strategy:
Define and lead a comprehensive AI strategy for Janus Henderson. Develop a vision for how data science, machine learning, and AI can support key business objectives, continuously refining the strategy based on emerging technologies and business needs.
Model Development & AI Innovation:
Lead a team of data scientists and AI engineers in developing predictive models and AI solutions, guiding the model development life cycle from POC to deployment, ensuring models deliver business value and are well maintained.
AI Governance & Ethics:
Establish an AI governance framework to ensure responsible use of AI, setting standards for model validation, transparency, fairness, and compliance with emerging AI regulations.
Enablement & Collaboration:
Encourage collaboration between the Data Science team and other units, acting as a bridge to integrate AI solutions into business processes.
Emerging Technology & Thought Leadership:
Keep the firm at the forefront of technological advances, monitor industry trends, lead innovation initiatives and pilot programs, and advocate for investments in data science capabilities that yield competitive advantage.
Must Have Skills
Education:
Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related quantitative field.
Experience:
10+ years in data science, analytics, or related technology roles, with at least 5 years in a leadership or managerial capacity, preferably in financial services, asset management, or capital markets.
Technical Proficiency:
Deep expertise in machine learning techniques, statistical modeling, and data analysis, including hands‑on experience developing and deploying predictive models, NLP, time‑series forecasting, and large‑dataset handling.
Industry Knowledge:
Solid understanding of asset‑management business, investment products, portfolio management processes, performance analytics, and how data and AI are used in investment management.
Leadership & Communication:
Demonstrated ability to lead teams of data scientists/analysts, manage complex projects, and present findings to senior executives and committees.
Nice to Have Skills
Asset Management Analytics:
Direct experience within an asset‑management firm’s analytics or quant research team.
AI Governance Implementation:
Experience establishing governance processes for AI/ML, such as forming model review committees or monitoring frameworks.
Advanced Analytics Tools:
Hands‑on familiarity with finance analytics ecosystems, quantitative finance libraries, time‑series databases, and visualization tools common in finance.
Innovation & Research:
Published work, patents, or conference presentations in AI or data science, particularly relating to finance.
Soft Skills & Leadership Competencies
Strategic Vision & Innovation:
Communicate a clear vision of how AI and analytics drive business value and anticipate future opportunities.
Ethical Leadership:
Advocate for responsible AI and model governance, ensuring adherence to fiduciary duties and ethical standards.
Communication & Storytelling:
Explain complex analytical concepts in plain language and produce clear documentation.
Collaboration & Influence:
Build relationships across IT, investment, compliance, and client teams to influence decisions at senior levels.
Mentorship & Talent Development:
Build a strong data science team, mentor junior members, and foster continuous learning.
Problem‑Solving & Resilience:
Approach data quality, model performance, and resource constraints methodically, iterating solutions under pressure.
Supervisory Responsibilities
Yes
Potential for growth
Mentoring
Leadership development programs
Regular training
Career development services
Continuing education courses
Compensation
The base salary range for this position is
$205,000–$215,000 . This range is estimated for this role. Actual pay may differ. The position will be posted through May 15, 2026.
Benefits
Hybrid working and reasonable accommodations
Generous holiday policies
Paid volunteer time
Professional development courses and tuition reimbursement
Diversity, equity and inclusion initiatives
Maternal/paternal leave benefits and family services
Complimentary subscription to Headspace
Corporate membership to ClassPass and other health benefits
Unique employee events and programs, including a 14er challenge
Complimentary beverages, snacks and all employee happy hours
Annual Bonus Opportunity
Position may be eligible to receive an annual discretionary bonus award from the profit pool. Individual bonuses are determined based on company, department, team, and individual performance.
EEO Statement
Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.
Compliance & Ethical Standards
You should be willing to adhere to the provisions of our Investment Advisory Code of Ethics related to personal securities activities and other disclosure and certification requirements.
Applicants’ past political contributions or activity may impact eligibility for this position.
Applicants will be expected to understand the regulatory obligations of the firm, and abide by the regulated entity requirements and JHI policies applicable to your role.
#J-18808-Ljbffr
Position Overview
The Head of Data Science & AI spearheads the asset management firm’s data‑driven initiatives, responsible for developing and executing a strategy to harness data and artificial intelligence across the organization. This role oversees advanced analytics, AI model development, and the governance of AI/ML usage, ensuring that the firm leverages AI ethically and effectively to gain insights—improving investment research, client experiences, and operations. It combines deep technical expertise with leadership and industry knowledge to transform data into a competitive advantage while upholding the strict standards of accuracy, transparency, and client trust expected in asset management.
Key Responsibilities
AI Strategy:
Define and lead a comprehensive AI strategy for Janus Henderson. Develop a vision for how data science, machine learning, and AI can support key business objectives, continuously refining the strategy based on emerging technologies and business needs.
Model Development & AI Innovation:
Lead a team of data scientists and AI engineers in developing predictive models and AI solutions, guiding the model development life cycle from POC to deployment, ensuring models deliver business value and are well maintained.
AI Governance & Ethics:
Establish an AI governance framework to ensure responsible use of AI, setting standards for model validation, transparency, fairness, and compliance with emerging AI regulations.
Enablement & Collaboration:
Encourage collaboration between the Data Science team and other units, acting as a bridge to integrate AI solutions into business processes.
Emerging Technology & Thought Leadership:
Keep the firm at the forefront of technological advances, monitor industry trends, lead innovation initiatives and pilot programs, and advocate for investments in data science capabilities that yield competitive advantage.
Must Have Skills
Education:
Master’s or Ph.D. in Computer Science, Data Science, Statistics, Engineering, or related quantitative field.
Experience:
10+ years in data science, analytics, or related technology roles, with at least 5 years in a leadership or managerial capacity, preferably in financial services, asset management, or capital markets.
Technical Proficiency:
Deep expertise in machine learning techniques, statistical modeling, and data analysis, including hands‑on experience developing and deploying predictive models, NLP, time‑series forecasting, and large‑dataset handling.
Industry Knowledge:
Solid understanding of asset‑management business, investment products, portfolio management processes, performance analytics, and how data and AI are used in investment management.
Leadership & Communication:
Demonstrated ability to lead teams of data scientists/analysts, manage complex projects, and present findings to senior executives and committees.
Nice to Have Skills
Asset Management Analytics:
Direct experience within an asset‑management firm’s analytics or quant research team.
AI Governance Implementation:
Experience establishing governance processes for AI/ML, such as forming model review committees or monitoring frameworks.
Advanced Analytics Tools:
Hands‑on familiarity with finance analytics ecosystems, quantitative finance libraries, time‑series databases, and visualization tools common in finance.
Innovation & Research:
Published work, patents, or conference presentations in AI or data science, particularly relating to finance.
Soft Skills & Leadership Competencies
Strategic Vision & Innovation:
Communicate a clear vision of how AI and analytics drive business value and anticipate future opportunities.
Ethical Leadership:
Advocate for responsible AI and model governance, ensuring adherence to fiduciary duties and ethical standards.
Communication & Storytelling:
Explain complex analytical concepts in plain language and produce clear documentation.
Collaboration & Influence:
Build relationships across IT, investment, compliance, and client teams to influence decisions at senior levels.
Mentorship & Talent Development:
Build a strong data science team, mentor junior members, and foster continuous learning.
Problem‑Solving & Resilience:
Approach data quality, model performance, and resource constraints methodically, iterating solutions under pressure.
Supervisory Responsibilities
Yes
Potential for growth
Mentoring
Leadership development programs
Regular training
Career development services
Continuing education courses
Compensation
The base salary range for this position is
$205,000–$215,000 . This range is estimated for this role. Actual pay may differ. The position will be posted through May 15, 2026.
Benefits
Hybrid working and reasonable accommodations
Generous holiday policies
Paid volunteer time
Professional development courses and tuition reimbursement
Diversity, equity and inclusion initiatives
Maternal/paternal leave benefits and family services
Complimentary subscription to Headspace
Corporate membership to ClassPass and other health benefits
Unique employee events and programs, including a 14er challenge
Complimentary beverages, snacks and all employee happy hours
Annual Bonus Opportunity
Position may be eligible to receive an annual discretionary bonus award from the profit pool. Individual bonuses are determined based on company, department, team, and individual performance.
EEO Statement
Janus Henderson Investors is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status. All applications are subject to background checks.
Compliance & Ethical Standards
You should be willing to adhere to the provisions of our Investment Advisory Code of Ethics related to personal securities activities and other disclosure and certification requirements.
Applicants’ past political contributions or activity may impact eligibility for this position.
Applicants will be expected to understand the regulatory obligations of the firm, and abide by the regulated entity requirements and JHI policies applicable to your role.
#J-18808-Ljbffr