
Data Scientist
1 week ago
**About the Role**:
As a Data Scientist, you'll be a key player in driving data-driven decision-making and innovation. You'll leverage your expertise in data analysis and machine learning to uncover valuable insights from complex datasets. Your work will have a direct impact in the entire customer lifecycle from Lead Management to Credit Decisioning to Collections & Monitoring.
**Responsibilities**:
- Collect, clean, and analyze large sets of structured and unstructured data to extract meaningful insights and trends
- Develop and implement advanced machine learning algorithms to solve complex business problems
- Support moving models to production, by creating high quality code modules that can be seamlessly integrated into existing systems (both on-prem and cloud)
- Communicate complex findings to both technical and non-technical audiences through effective data visualization and storytelling.
- Collaborate with cross-functional teams to identify data-driven opportunities and translate business requirements into actionable data solutions.
- Support the development and maintenance of data pipelines and infrastructure
- Stay up-to-date with industry trends and advancements in Data Science and Machine Learning technologies
**Skills Required**:
- Strong foundation in statistics, and machine learning algorithms
- Strong proficiency in programming languages like Python and SQL.
- Excellent problem-solving and analytical skills.
- Ability to work independently and as part of a team.
- Should have built production models using at least 2 of the ML techniques: Clustering, Regression, Classification
- Experience in Banking & Financial Services is preferred.
- Experience working on cloud platforms (e.g., AWS, GCP) is preferred.
- A passion for data and a curiosity to explore new trends and technologies
**Education Requirements**: Graduate-level qualification in Engineering /Data Science
**Work Experience**:3+ years of relevant experience in data science and analytics, with a track record of developing and deploying ML models into production.
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