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Senior Developer, Data Science
3-7 years
Hyderabad / Secunderabad
1 vacancy
Senior Developer, Data Science
International Centre for Excellence
posted 3mon ago
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Job Description
Intercontinental Exchange, Inc. (ICE) presents an opportunity for a full-time Senior developer to join a team responsible for development of the platform for providing cutting edge AI and ML solutions across the enterprise. The Senior Developer will have experience in all phases of software development lifecycle, from requirements gathering, to design, coding, unit testing, debugging, and supporting in production.
The candidate will be part of a newly formed ICE AI Center of Excellence team, key to ICE s long-term strategy to incorporate Gen AI technologies in our solutions in a responsible and sustainable way across the enterprise. The ideal candidate should be knowledgeable in designing and developing solutions using the modern advancements in Gen AI, database systems and scripting languages.
This position requires technical proficiency/problem solving as well as an eager attitude, professionalism, and solid communication skills. Strong written and oral communication is required as the applicant will frequently be interacting with the diverse teams across the enterprise to achieve business goals.
Responsibilities
On any day, the candidate could be doing any or all of the following:
- Analyze requirements and propose data-driven technical solutions in delivering projects within expected parameters of cost, time, and quality.
- Design, develop, and maintain scalable data science models and algorithms using modern technologies (e.g., Python, R, TensorFlow, PyTorch).
- Create and manage large-scale data pipelines, ensuring data integrity and security.
- Develop and validate predictive models, perform statistical analysis, and interpret complex data sets.
- Work with project managers to compile a work breakdown structure of tasks for a given deliverable and provide realistic estimates for completing the assignment.
- Collaborate with other Data Scientists, Developers, and QA Engineers to execute full cycle integration, functional, and regression testing of data science solutions.
- Continuously improve model performance and propose innovative solutions to complex problems.
- Effectively interact with business and operations for solving data-related challenges and translating business requirements into technical solutions.
- Develop and maintain data visualizations and dashboards to communicate insights to stakeholders.
- Implement and integrate machine learning models into production environments, ensuring scalability and robustness.
- Ensure cross-functional collaboration and knowledge sharing within the team and with other departments.
- Maintain code quality, organization, and automation for data science projects.
- Participate in code reviews, provide constructive feedback to peers, and mentor junior team members.
- Stay up-to-date with emerging data science technologies, techniques, and industry trends to continuously improve skills and project outcomes.
Knowledge and Experience
- Advanced degree (PhD preferred, MS with significant experience) in a quantitative field such as Computer Science, Electrical Engineering, Information Sciences, Statistics, Mathematics, Economics, Operations Research, or a related field with a focus on data-driven statistical analysis and modeling.
- Strong, proven programming skills in at least one general-purpose programming language such as Python, R, Java, or C++.
- Extensive experience with data science libraries and tools (e.g., Pandas, NumPy, SciPy, Scikit-learn, TensorFlow, PyTorch).
- Proficiency in SQL and experience with database management and data manipulation.
- Experience with big data technologies such as Spark, Hadoop, and data formats like PARQUET.
- Experience with data visualization and business analytics tools like Tableau, PowerBI, or similar tools.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud, including data services like AWS S3, Redshift, Azure Data Lake, or Google BigQuery.
- Familiarity with data engineering concepts and tools (e.g., Apache Airflow, Kafka).
- Solid understanding of version control tools (ideally Git) and collaborative coding practices.
- Experience in applying data-driven statistical analysis and modeling solutions to real-world problems, preferably in a financial context.
- Proven ability to write complex programs and implement custom algorithms.
- Experience with deploying machine learning models into production environments and ensuring their scalability and performance.
- Knowledge of continuous integration and continuous deployment (CI/CD) pipelines for data science projects.
- Excellent communication skills (oral and written) to explain complex algorithms and solutions to stakeholders across multiple disciplines and to work effectively in a diverse team.
- Experience in an applied R&D environment, working in an agile and innovation-lab culture.
Employment Type: Full Time, Permanent
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