Data Scientist Architect

Creative Synergies Group; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Creative Synergies Group in Bengaluru seeks an accomplished Lead Data Architect to drive strategic data planning, architecture design, and scalable pipelines for growing data needs. You will collaborate with cross-functional teams to ensure alignment with business goals and to deploy analytics solutions.

Lead the governance framework, mentor data scientists and engineers, and oversee ML lifecycle initiatives, ensuring compliance and scalable performance across the organization.

Qualifications

• Proven experience designing data architectures at scale.
• Strong programming and data processing skills.
• Experience with ML lifecycle and MLOps practices.
• Ability to govern data quality, privacy, and security.

Responsibilities

• Lead strategic data planning and architecture development.
• Design scalable data pipelines and architectures.
• Collaborate with cross‑functional teams to align with business goals.
• Develop and deploy ML models and analytics solutions.
• Establish data governance policies and regulatory compliance.
• Mentor junior data scientists and engineers.

Skills

Python/Scala

R

Spark/Hadoop

SQL/NoSQL

ML/DS modelling

Data governance

Cloud (AWS/Azure/GCP)

MLOps

NLP basics

Docker/Kubernetes

Git/version control

Streaming data (Kafka/Flink)

Education

Bachelor’s or Master’s in CS/Math/Stats

Tools

AWS/Azure/GCP

Kafka

Spark

Hadoop

Flink

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.