Data Scientist Architect

Creative Synergies Group; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

A leading technology firm in Bengaluru is seeking an experienced Data Scientist to lead data architecture strategies and implement machine learning solutions. The ideal candidate has 12-14 years of experience in data science and a deep understanding of software engineering principles. This role involves collaboration with cross-functional teams and requires strong communication skills. The company offers competitive compensation and opportunities for growth.

Qualifications

• 12-14 years of experience in data science with architecture focus.
• Proven expertise in data architectures and solutions.
• Excellent communication skills for technical concepts.
• 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 for stakeholders.
• Leadership experience leading cross-functional teams and driving strategic initiatives.

Responsibilities

• Lead the development of data architecture strategy.
• Develop and deploy machine learning models.
• Establish data governance policies.
• Develop and deploy machine learning models and algorithms to extract actionable insights.
• Apply statistical techniques and advanced analytics to solve business problems.
• Innovate in NLP, deep learning, and predictive modeling to stay ahead in data science.
• Establish and enforce data governance policies for quality, integrity, and security.
• Ensure compliance with regulatory requirements (GDPR, HIPAA, CCPA).
• Architect robust model deployment pipelines for production environments.
• Collaborate with IT and DevOps to deploy and monitor models at scale.
• Mentor junior data scientists and analysts; foster innovation and continuous learning.

Skills

Machine Learning

Deep Learning

Python

Data Visualization

Big Data Technologies

Software Engineering Principles

Big Data

Spark

Kafka

Docker

Kubernetes

Git

MLOps

NLP

Software Engineering

Education

Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics

Tools

SQL

NoSQL

Docker

Kubernetes

Apache Spark

AWS

Git

Docker

Kubernetes

Job description

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.