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- Tasks: Lead AI and ML projects for investment and market research, enhancing decision-making.
- Company: Join a forward-thinking firm focused on data-driven investment strategies.
- Benefits: Enjoy a hybrid work model with flexibility and opportunities for professional growth.
- Why this job: Be at the forefront of innovation in finance, collaborating with top professionals.
- Qualifications: 8+ years in data science, with strong skills in AI/ML and cloud technologies required.
- Other info: Mentorship opportunities available for junior team members.
The predicted salary is between 43200 - 72000 £ per year.
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Location: Hybrid role based in Toronto/Waterloo (3 days per week in office)
As the successful candidate, you will be responsible for leading the AI and ML related work around Investment and Market Research for driving our vision around data driven decision making across portfolios and ecosystem. You will be responsible for designing, developing, and implementing generative AI and ML based solutions to enhance our asset management capabilities. You will work closely with our investment professionals, data scientists, and IT team to identify and address complex challenges, optimize investment strategies, and drive innovation within the firm.
ACCOUNTABILITIES:
- Develop and deploy cutting-edge AI and machine learning models to support investment decision-making, portfolio optimization, and risk management.
- Collaborate with cross-functional teams to understand business requirements and translate them into effective AI-driven solutions.
- Implement and maintain robust data pipelines, ensuring the integrity, security, and accessibility of data used for AI/ML applications by working with the Data Platform.
- Working with the Cloud Engineering team, continuously research and evaluate emerging AI/ML techniques, tools, and technologies to identify opportunities for improvement and innovation.
- Provide technical leadership and mentorship to junior team members, contributing to the growth and development of the AI/ML capabilities within the firm.
- Ensure the scalability, reliability, and performance of AI/ML systems, optimizing for efficiency and cost-effectiveness.
- Participate in the development of AI/ML governance policies and best practices to ensure compliance with regulatory requirements and industry standards.
- Inner sourcing: Partnering with Enterprise teams, drive the needs of the organization by creating a collaborative development approach.
QUALIFICATIONS:
- 8+ years’ experience in data-driven organizations with a focus on end-to-end data science related initiatives.
- 4+ years hands-on experience building applications, data platform and pipelines in cloud-native technologies. Deep technical understanding of Data and Analytics paradigms and technologies – Cloud (AWS, Azure), Databases/Warehouses (Snowflake, Oracle), etc.
- Extensive experience (5+ years) in designing and implementing AI/ML solutions, preferably in the financial services or asset management industry.
- Hands on experience with LLM and embedding models
- Strong programming skills, particularly in Python, experience with Machine Learning frameworks like TensorFlow, PyTorch, or Keras, and familiarity with cloud-based AI/ML platforms.
- Understanding of agent-based AI architectures, agent orchestration, multi-agent frameworks and hybrid RAG-CAG architectures.
- Bachelor\’s or master\’s degree in computer science or related technical field.
- Proven understanding of modern Digital & CRM technologies.
- Demonstrated ability to communicate, negotiate, influence, and arbitrate competing priorities within a diverse set of user communities and stakeholders (internal and external).
- Strong decision making, outcome driven, influencing, leading change and communication skills.
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AI Engineer - 5364 employer: S.i. Systems
Contact Detail:
S.i. Systems Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - 5364
✨Tip Number 1
Network with professionals in the AI and finance sectors. Attend industry meetups, webinars, or conferences to connect with potential colleagues and learn about the latest trends in AI applications within asset management.
✨Tip Number 2
Showcase your hands-on experience with cloud-native technologies by contributing to open-source projects or building your own AI/ML applications. This practical experience can set you apart from other candidates.
✨Tip Number 3
Familiarise yourself with the specific AI/ML tools and frameworks mentioned in the job description, such as TensorFlow and PyTorch. Consider taking online courses or certifications to deepen your knowledge and demonstrate your commitment to continuous learning.
✨Tip Number 4
Prepare for interviews by practising how to explain complex AI/ML concepts in simple terms. Being able to communicate effectively with non-technical stakeholders is crucial in this role, so focus on honing your communication skills.
We think you need these skills to ace AI Engineer - 5364
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI and machine learning, particularly in investment and market research. Emphasise your hands-on experience with cloud-native technologies and programming skills in Python.
Craft a Compelling Cover Letter: In your cover letter, explain why you are passionate about AI in the financial services sector. Mention specific projects or achievements that demonstrate your ability to develop and implement AI/ML solutions.
Showcase Technical Skills: Clearly outline your technical skills related to AI/ML frameworks like TensorFlow or PyTorch. Include any experience with data pipelines and cloud platforms such as AWS or Azure, as these are crucial for the role.
Highlight Collaboration Experience: Since the role involves working closely with cross-functional teams, provide examples of past collaborations. Discuss how you’ve translated business requirements into effective AI-driven solutions, showcasing your communication and leadership skills.
How to prepare for a job interview at S.i. Systems
✨Showcase Your Technical Expertise
Be prepared to discuss your hands-on experience with AI and ML frameworks like TensorFlow or PyTorch. Highlight specific projects where you've developed and deployed models, especially in the financial services sector.
✨Demonstrate Collaboration Skills
Since the role involves working closely with cross-functional teams, share examples of how you've successfully collaborated with data scientists, IT teams, or investment professionals to achieve common goals.
✨Discuss Data Pipeline Management
Talk about your experience in implementing and maintaining data pipelines. Be ready to explain how you ensure data integrity and security, particularly in cloud-native environments like AWS or Azure.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills. Prepare to discuss how you would approach complex challenges in investment decision-making or portfolio optimisation using AI-driven solutions.
