Senior Data Scientist

Job Title: Senior Data Scientist
Location: Bangalore
Experience: 8 - 12 Years

Job Summary

We are seeking a highly skilled and experienced Senior Data Scientist to join our team in Bangalore. The ideal candidate will have a deep understanding of Machine Learning (ML) and Artificial Intelligence (AI), with a strong focus on Azure Fabric within the banking and finance domain. In this role, you will develop and implement advanced data-driven solutions that enhance decision-making, optimise processes, and contribute to the success of our client’s financial objectives.

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 big data technologies and cloud platforms (Azure, AWS).
• Proficiency in Python-related data science libraries (e.g., Pandas, NumPy, Scikit-learn).
• Experience in data processing, ETL pipelines, and data engineering.
• Familiarity with SQL and NoSQL databases.

Key Responsibilities

• Design and implement Machine Learning (ML) and 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 optimise 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: Bachelor’s/Master’s 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.
• Proficient in Python, R, and data science libraries (Pandas, Scikit-learn, TensorFlow).
• Experience in AI and Deep Learning models, including neural networks.
• Working knowledge of big data technologies such as Spark, Hadoop, and Databricks.
• Familiarity with SQL and NoSQL databases.
• Experience with version control systems (Git, GitHub, etc.).

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

• Experience in the banking or financial services industry.
• 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.

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.

Compensation & Benefits

• Competitive salary and annual performance-based bonuses
• Comprehensive health and optional Parental insurance.
• Retirement savings plans and tax savings plans.
• Work-Life Balance: Flexible work hours

KRA (Key Result Areas)

• Timely and effective delivery of ML/AI models that solve complex business problems.
• Continuous improvement and optimisation 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.

KPI (Key Performance Indicators)

• Number of successful ML/AI models deployed and their performance post-deployment.
• Model accuracy and predictive capability (based on business goals).
• Client feedback on AI-driven solutions.
• Completion time for delivering actionable data-driven insights.
• Team collaboration and mentoring effectiveness with junior data scientists.

Contact: hr@bigtappanalytics.com