Senior Data Scientist - Machine Learning/Artificial Intelligence

Primary Skills : Machine Learning, Artificial Intelligence, AZURE, Python, Databricks

Secondary Skills : Cloud Automation

Degree : ANY graduate

Job Summary :

We are seeking an experienced Senior Data Scientist with a strong background in traditional Machine Learning (ML), AI, and expertise in Azure Fabric to work in the Finance Department of a Bank. The ideal candidate will play a key role in applying advanced analytics to drive business insights, improve processes, and enhance decision-making in the banking sector. The candidate should be proficient in ML models and AI technologies with a focus on real-world banking applications and have hands-on experience with Azure Fabric.

Mandatory Skills :

- Proven experience in traditional Machine Learning (ML) and Artificial Intelligence (AI).

- Strong experience in Azure Fabric and its integration with various banking systems.

- Expertise in Data Science methodologies, predictive modelling, and statistical analysis.

- Solid understanding of the Finance domain with a focus on banking processes and challenges.

- Hands-on experience with cloud platforms (Azure).

- Experience in the banking or financial services industry.

Key Responsibilities :

- Design and implement Machine Learning (ML) and Traditional Artificial Intelligence (AI) models to solve complex business problems in the finance sector.

- Work closely with business stakeholders to understand requirements and translate them into data-driven solutions.

- Develop and deploy ML models on Azure Fabric, ensuring their scalability and efficiency.

- Analyze large datasets to identify trends, patterns, and insights to support decision-making.

- Collaborate with cross-functional teams to integrate AI/ML solutions into business processes and banking systems.

- Maintain and optimize deployed models and ensure their continuous performance.

- Keep up to date with industry trends, technologies, and best practices in AI and ML, specifically within the

finance industry.

Qualifications :

Education : Bachelors/Masters degree in Computer Science, Data Science, Engineering, or related field.

Certifications : Relevant certifications in Data Science, Azure AI, or Machine Learning is a plus.

Technical Skills :

- Expertise in Machine Learning (ML) algorithms (Supervised and Unsupervised).

- Strong experience with Azure Fabric and related Azure cloud services.

- Familiarity with Python and data science libraries (Pandas, Scikit-learn, TensorFlow).

- Experience in AI and Deep Learning models, including neural networks.

Soft Skills :

- Excellent problem-solving and analytical skills.

- Strong communication skills, with the ability to present complex data insights clearly to non-technical stakeholders.

- Ability to work effectively in a collaborative, cross-functional environment.

- Strong attention to detail and ability to manage multiple tasks simultaneously.

- A passion for continuous learning and staying updated on new technologies.

Good to Have :

- Familiarity with DevOps practices for ML/AI model deployment.

- Knowledge of cloud-native architecture and containerization (Docker, Kubernetes).

- Familiarity with Deep Learning and Natural Language Processing (NLP) techniques.

- Familiarity with SQL and NoSQL databases.

- Experience with version control systems (Git, GitHub, etc.).

Work Experience :

- 8-12 years of experience in Data Science, with hands-on experience in ML, AI, and working within the finance or banking industry.

- Proven track record of designing and deploying machine learning models and working with Azure Fabric.

- Experience with client-facing roles and delivering solutions that impact business decision-making.

KRA (Key Result Areas) :

- Timely and effective delivery of ML/AI models that solve complex business problems.

- Continuous improvement and optimization of deployed models.

- High-quality insights and data-driven solutions delivered for business stakeholders.

- Client satisfaction with AI/ML solutions implemented within the banking domain