Data Scientist II

2 weeks ago

Mumbai, India RELX India (Pvt) Ltd Risk div Company Full time
About the role
Data Scientist II in our vibrant and forward-thinking Innovation Engineering Group, you will be at the forefront of using advanced data analysis and modelling techniques to drive innovative solutions.
Responsibilities:
Participating in end-to-end modelling projects, handling large variety and volume of data.
Conducting exploratory data analysis, feature construction, and feature engineering.
Developing and evaluating advanced predictive models using Python, Kera’s, TensorFlow, and other relevant technologies.
Focusing on specialty areas such as Anomaly Detection, Time Series Forecasting, NLP and Generative AI.
Deploying models and monitoring their performance post-deployment.
Conducting proof-of-concept research to explore new modelling techniques and methodologies.
Collaborating closely with software engineers and other team members to integrate models into larger systems.
Continuously seek to innovate and bring cutting-edge solutions to our customers.
Developing high-quality data-driven solutions.
Collaborating effectively within a multidisciplinary team environment.
Staying abreast of the latest advancements in data science and related technologies.
Delivering presentations and reports on findings and translating complex concepts into actionable insights.
Mentoring junior data scientists and contribute to team knowledge sharing.
All other duties as assigned.
Requirements:
1+ years of Data Science experience
BS Engineering/Computer Science/Data Science or equivalent experience required.
Strong problem-solving and analytical skills.
Proficiency in Python and libraries/frameworks like Kera’s and TensorFlow.
Strong understanding of machine learning algorithms and statistical modelling techniques.
Experience in handling large datasets and proficiency in data manipulation.
Ability to translate complex data science concepts into practical solutions.
Excellent communication skills, both oral and written.
Designing test strategies, plans and processes, methodologies and supporting documentation for functional and non-functional areas
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