Data Scientist Architect
Full Time
Bangalore
Posted 5 months ago
Role | Data Scientist Architect |
Experience | 9 – 15 Years |
Educational Qualification | B.E / B. Tech, M.E/ M. Tech |
Location | Bangalore |
Technical Competencies | Machine Learning, Deep Learning, Python, Spark, Deployment, AI, NLP, Tensorflow/Pytorch, Database, OLAP |
Responsibilities:
Strategic Data Planning and Architecture:
- Lead the development of our data architecture strategy, encompassing data collection, storage, processing, and analysis.
- Design scalable and efficient data pipelines and architectures to support our growing data needs.
- Collaborate with cross-functional teams to ensure alignment with business goals and objectives.
Advanced Analytics and Modeling:
- Develop and deploy sophisticated machine learning models and algorithms to extract actionable insights from complex datasets.
- Apply statistical techniques and advanced analytics to solve business problems and drive decision-making.
- Innovate in areas such as deep learning, natural language processing, and predictive modeling to stay at the forefront of data science.
Data Governance and Compliance:
- Establish and enforce data governance policies and best practices to ensure data quality, integrity, and security.
- Ensure compliance with regulatory requirements such as GDPR, HIPAA, and CCPA.
- Implement data privacy and anonymization techniques to protect sensitive information.
Model Deployment and Integration:
- Architect robust model deployment pipelines for seamless integration into production environments.
- Collaborate with IT and DevOps teams to deploy and monitor models at scale.
- Optimize model performance and scalability for real-time inference and decision-making.
Leadership and Mentorship:
- Provide technical leadership and guidance to junior data scientists and analysts.
- Foster a culture of innovation, collaboration, and continuous learning within the data science team.
- Act as a subject matter expert on data science and architecture, both internally and externally.
Required Skills/Experience:
- Proficiency in programming languages such as Python, R, or Scala, with a focus on data manipulation, analysis, and modeling.
- Expertise in data visualization tools and libraries such as Matplotlib, Seaborn, Plotly, or D3.js.
- Deep understanding of database technologies including SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra).
- Experience with big data technologies such as Hadoop, Spark, or Kafka for processing and analyzing large datasets.
- Knowledge of distributed computing frameworks such as Apache Hadoop, Apache Spark, or Apache Flink.
- Familiarity with containerization technologies such as Docker and container orchestration tools like Kubernetes.
- Experience with version control systems such as Git for code management and collaboration.
- Strong understanding of software engineering principles, including modular design, testing, and debugging.
- Knowledge of agile methodologies and experience working in agile development environments.
- Familiarity with data engineering concepts and tools for data ingestion, transformation, and cleansing.
- Experience with streaming data technologies and real-time data processing frameworks (e.g., Apache Kafka, Apache Flink, Apache Storm).
- Understanding of machine learning operations (MLOps) principles and practices for managing machine learning lifecycle.
- Familiarity with natural language processing (NLP) techniques and libraries such as NLTK, spaCy, or TensorFlow.
Qualification:
- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or related field.
- 12-14 years of experience in data science, with a focus on architecture and design.
- Proven expertise in designing and implementing data architectures and solutions at scale.
- Strong proficiency in machine learning, statistical analysis, and data mining techniques.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
- Excellent communication and interpersonal skills, with the ability to communicate complex technical concepts to non-technical stakeholders.
- Leadership experience, with a track record of leading cross-functional teams and driving strategic initiatives.
Job Features
Job Category | Intelligent Connected Products |