Data Scientist

2 months ago

Bengaluru, India JPMorgan Chase & Co. Full time

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in the Data Analytics team to partner with the Business.

As a Data Scientist - Core Analytics Associate within our team, you will lead our data strategy, applying advanced statistical techniques and developing machine learning models. 

Job Responsibilities:

Lead Data Strategy: Take ownership of defining and executing the data strategy, including identifying opportunities for leveraging data to drive business value and competitive advantage. Apply advanced statistical techniques, including predictive modelling, time series analysis, and optimization algorithms, to extract insights from complex data sets. Develop and deploy machine learning models for various use cases such as customer segmentation, churn prediction, recommendation systems, and anomaly detection. Explore and preprocess large, unstructured datasets using tools like Spark and Hadoop, and create compelling visualizations to communicate findings effectively to both technical and non-technical stakeholders. Cross-functional Collaboration: Collaborate closely with cross-functional teams including product management, engineering, and business stakeholders to identify key business problems, design solutions, and drive implementation. Model Deployment and Monitoring: Implement production-ready solutions by deploying machine learning models into scalable, real-time environments, and establish monitoring processes to ensure model performance and reliability over time. Mentorship and Leadership: Provide mentorship and technical guidance to junior data scientists, promote best practices in data science methodologies, and contribute to the professional development of the team. Continuous Learning: Stay updated with the latest trends and advancements in data science, machine learning, and related fields, and actively seek opportunities to enhance skills and knowledge.

Required qualifications, skills and capabilities:

Required : A master’s or . degree in Data Science, Computer Science, Statistics, Mathematics, or a related field, demonstrating a strong foundation in quantitative methods and analytical thinking. Minimum 8 years of experience in data science and data engineering, building data pipelines and driving data driven initiatives Expertise in Programming and Tools: Proficiency in programming languages such as Python or R, along with experience using data manipulation libraries like Pandas and NumPy, and familiarity with machine learning frameworks such as TensorFlow or PyTorch. Deep Understanding of AI/ML Techniques: Extensive hands-on experience with a wide range of AI/ML algorithms and techniques, including supervised and unsupervised learning, deep learning, reinforcement learning, and ensemble methods. Big Data Technologies: Experience working with big data technologies such as Apache Spark, Hadoop, or distributed computing frameworks, and proficiency in querying and manipulating large datasets using SQL or NoSQL databases. Data Visualization and Communication Skills: Strong ability to translate complex technical concepts and analysis results into clear and actionable insights, using data visualization tools like Matplotlib, Seaborn, Plotly, or Tableau. Business Acumen: Demonstrated experience in understanding business problems, defining analytical approaches, and delivering actionable recommendations to drive strategic decision-making and business growth.

Preferred qualifications, skills and capabilities:

Programming Languages – Python (Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch) Machine Learning Frameworks –NLP, TensorFlow; PyTorch Big Data Technologies – Apache Spark; Hadoop Data Visualization – Matplotlib, Seaborn, Plotly, Tableau Database and Querying – SQL, PostgreSQL, MongoDB Version Control and Collaboration – Git, GitHub Working knowledge of CI/CD & MLOps

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