Other
Posted 7 days ago
Deloitte rating
8.1
Based on 86 frontline employees who took The Breakroom Quiz
59th of 137 rated financial services
Job description
Data Scientist -Project Delivery Senior Analyst - AI & Engineering
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Delivery Talent Model is designed for professionals with specialized skills that align to a current client's need. Team members focus on delivering services to clients, without additional expectations related to business development or promotion. Their employment is tied to their role on a project, and they are eligible for a benefits package that is competitive for project delivery-focused professionals.
Recruiting for this role ends on June 22nd 2026
Work you'll do/Responsibilities
The Data Scientist will analyze, cleanse, and model complex data to help organizations make better decisions and predict future trends.
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
The Team
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required
- 4+ years of experience Proficiency with Python, statistical modeling, and machine learning frameworks (e.g. scikit-learn, PyTorch, TensorFlow).
- 4+ years of experience with feature engineering, model development, validation, and deployment.
- 4+ years of experience Understanding of MLOps pipelines, model versioning, monitoring, and retraining processes.
- 4+ years of experience Ability to translate complex business problems into analytical solutions with measurable outcomes.
- 4+ years of experience Strong knowledge of data wrangling, exploratory analysis, and visualization.
- 4+ years of experience Familiarity with cloud ML services (e.g. SageMaker, Azure ML, Fabric ML).
- 4+ years of experience communicating and explaining insights and model behavior to non-technical stakeholders
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Limited immigration sponsorship may be available
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Preferred
- Analytical/ Decision Making Responsibilities
- Analytical ability to manage multiple projects and prioritize tasks into manageable work products
- Can operate independently or with minimum supervision
- Excellent Written and Communication Skills
- Ability to deliver technical demonstrations
Data Scientist -Project Delivery Senior Analyst - AI & Engineering
Are you an experienced, passionate pioneer in technology who wants to work in a collaborative environment? As an experienced Data Scientist, you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. The Project Delivery Talent Model is designed for professionals with specialized skills that align to a current client's need. Team members focus on delivering services to clients, without additional expectations related to business development or promotion. Their employment is tied to their role on a project, and they are eligible for a benefits package that is competitive for project delivery-focused professionals.
Recruiting for this role ends on June 22nd 2026
Work you'll do/Responsibilities
The Data Scientist will analyze, cleanse, and model complex data to help organizations make better decisions and predict future trends.
- Communicate regularly with Engagement Managers (Directors), project team members, and representatives from various functional and / or technical teams, including escalating any matters that require additional attention and consideration from engagement management
The Team
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.
Qualifications
Required
- 4+ years of experience Proficiency with Python, statistical modeling, and machine learning frameworks (e.g. scikit-learn, PyTorch, TensorFlow).
- 4+ years of experience with feature engineering, model development, validation, and deployment.
- 4+ years of experience Understanding of MLOps pipelines, model versioning, monitoring, and retraining processes.
- 4+ years of experience Ability to translate complex business problems into analytical solutions with measurable outcomes.
- 4+ years of experience Strong knowledge of data wrangling, exploratory analysis, and visualization.
- 4+ years of experience Familiarity with cloud ML services (e.g. SageMaker, Azure ML, Fabric ML).
- 4+ years of experience communicating and explaining insights and model behavior to non-technical stakeholders
- Bachelor's degree, preferably in Computer Science, Information Technology, Computer Engineering, or related IT discipline; or equivalent experience
- Limited immigration sponsorship may be available
- Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
Preferred
- Analytical/ Decision Making Responsibilities
- Analytical ability to manage multiple projects and prioritize tasks into manageable work products
- Can operate independently or with minimum supervision
- Excellent Written and Communication Skills
- Ability to deliver technical demonstrations
Frequently asked questions
Q: What skills or qualities help someone succeed as a HRIS Data Architect and Data Warehouse Developer?
A: To succeed as a HRIS Data Architect and Data Warehouse Developer, key technical skills include proficiency in data modeling, data warehousing tools such as ETL (Extract, Transform, Load) software, and programming languages like SQL, Python, or Java. Additionally, strong analytical, problem-solving, and communication skills are essential, as well as the ability to collaborate with stakeholders and technical teams to design and implement data solutions. These strengths enable HRIS Data Architects and Data Warehouse Developers to effectively manage complex data systems, drive business insights, and support organizational growth.
Q: What is the career path for a HRIS Data Architect and Data Warehouse Developer?
A: A typical career progression for a HRIS Data Architect and Data Warehouse Developer involves starting as a Data Analyst or Business Intelligence Developer, then advancing to a Data Architect or Senior Data Analyst role, and eventually becoming a Lead Data Architect or Enterprise Data Architect. Key opportunities for skill development include learning data governance, cloud-based data platforms, and advanced data visualization tools, as well as developing expertise in data modeling, data warehousing, and business intelligence. Long-term career prospects may include transitioning into executive roles such as Chief Data Officer or Chief Information Officer, or pursuing specialized roles like Data Scientist or Business Intelligence Manager.
