Ovations Technologies
We are looking for an experienced Senior Data Scientist with strong AI/ML expertise to join our dynamic team in the Banking/FinTech space. This role is ideal for someone who thrives in data-driven environments, enjoys solving complex problems, and has experience delivering production-ready AI/ML solutions.
Minimum Requirements
Experience
5 or more years of relevant work experience as a Data Engineer/ Data Scientist
4–6+ years applied data science; 2+ years owning production AI/ML.
At least 3 years experience within a non-traditional FinTech, Banking or Financial Services Sector Consistent improvement CI/CD applications for collaborations and enhancement to drive develop once and deploy to many mindset through container repositories
Experience in Data Science and Data Analysis with a specific focus on AI/ ML models within banking, finance and/or telecommunications industry
Proven delivery of automated decisioning (recommendation/propensity/fraud/forecasting) with quantified business impact. Experience in Data Engineering within banking or financial services industry Understanding of enterprise-scale systems and technologies used in data infrastructures
Experience of working in an Agile/DevOps environment
GitHub or GitLab experience for CI/CD
Consistent improvement CI/CD applications for collaborations and enhancement to
drive develop once and deploy to many mindset through container repositories
Proficiency in working with Python and its relevant libraries SAS or R / Scala for data
clean up and advanced data analytics – Working knowledge in Hadoop, Apache Spark and related Big Data technologies
(MapReduce, PIG, HIVE) – Demonstrated experience utilizing software tools to query and report data and being
software agnostic – Highly proficient in database management systems like Postgres, Oracle, Mongo,
MSSQL – Experience in data analysis and management, business performance management
and/or reporting within the financial sector or banking industry – Experience working in a medium to large organization – Experience in ecommerce and electronic payment business is advantageous – Experience working across global locations/ regions and have a grasp of political, social, infrastructure and integrity challenges
Proficiency in working with data engineering capabilities that leverages both cloud
(Azure, GCP or AWS) and on-premise infrastructure. – CI/CD orchestrations and repository – Proficient in working with open-source languages such as Python, Jupyter Notebook,
R / Spark – Scala and others to drive optimized data engineering and machine
learning best practise frameworks – Strong analytical skills with ability to automate reports that tells a story through
visualization by leveraging standard enterprise BI tools like Power BI, Data Studio,
Elastic Search-Kibana and many others – Working knowledge in Hadoop, Apache Spark and related Big Data technologies and
their applications in data engineering and MLOps pipelines – Highly proficient in data warehouse and management for RDBMS and latest Big Data
capability – Ability to design, deploy and maintain machine learning and predictive model for different business use cases
Data Engineering, Mining and analytics – AI/ Machine learning for predictive modelling and other relevant use cases – Payment, E-Commerce and digital platforms – Understanding of FinTech, banking, microfinance and payment business
Qualifications
Minimum of 4-year tertiary degree in Computer Science, Mathematics, Statistics, Data Science or related field
Masters Degree in a Data Science, AI/ML, Statistical or related field (preferred)
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