Senior Data Science Manager, Data Engineering & Big Data Head, Global Delivery Head, BI / Data Analy
Onpassive Technologies Private Limited, Hyderabad/ Dubai/ Singapore/ USA
مجموع سنوات الخبرة :18 years, 9 أشهر
Leading a talented group of Data Scientists, Big data Engineers, Product Owners & Cloud Engineers, delivering ML & AI solutions to production, hiring and heading a diverse team also managing implementation, CI/ CD and application monitoring. AI/ML, Data Science, Big data, Data Engineering, Data Analytics, DevOps, Cloud Platforms and Web technologies (UI/UX and backend skills). Experience with Solution designing, developing, and deploying Machine Learning models using Cloud Platform. Management of data pipelines including config, ingestion and transformation from multiple data source like Big Query, Dbt & Google cloud storage etc. Re-Training and Monitoring Pipeline setup with multiple criteria Vertex AI.
Analysing all projects and ensuring compliance with project schedules, delivering all projects efficiently within budget and time frame, coordinating with stakeholders to ensure project deliverable s are aligned with business requirements, and documenting all project deliverable s. Working on Amazon Web Services (AWS), Azure Cloud, and Google Cloud (GCP). Automated deployment using CI/CD tools. Build new analytics solutions along with demos and prototypes as relevant for the target industries and buyers.
Worked on frameworks such as Tensorflow, Pytorch, Keras, Scikit-learn, etc., Collaborated with cross-functional teams to ensure the successful implementation of data-driven solutions. Acted as a key liaison between the US commercial team and the India-based data science team. Designed, built, and deployed deep learning models using various programming languages such as Python, Spark, TensorFlow, and PyTorch etc., Development of end-to-end MLOps framework and Machine Learning Pipeline using GCP, Vertex AI and Software tools. Serving Pipeline with multiple creation Vertex AI and GCP services.
Working with Data Visualization tool such as Tableau, Power BI, BigQuery etc. NLP - Conversational AI/Chat Bots. Developed strategy plan and roadmap for the Databricks Center of Excellence aligned with the organization's goals and objectives. Defined the COE's vision, mission, and key performance indicators (KPIs). Identified areas of opportunity and growth for Databricks within the organization. Management of Hadoop cluster and cloud platforms like Snowflake.
Worked on LLM models (GPT, LLaMA, BLOOM, BERT, T5, PaLM, Meta, Google Gen AI Studio etc). Worked on AI Cloud Tools (AWS Sage Maker, Tensor Flow, PyTorch, MS Azure, OpenAI, Hugging Face), MLOps/AIOps (domino, mlflow), Low Code RPA (Appian, UI Path), Big Data, Python, Java JS, Full Stack, No SQL, API, Docker & Kubernetes. Meta Data and statistics Data pipeline setup using GCP Bucket and MLMD. Resource and Infra Monitoring configuration and pipeline development using GCP service.
Managed end-to-end deliveries and implementation of DE solutions both on-prem & on cloud. Responsible for partnering with US and India leads, developing DE delivery teams, and bringing data management best practices to solve client business problems. Automated pipeline Development for Continuous Integration (CI)/Continuous Deployment. (CD) Continuous Monitoring (CM)/Continuous Training (CT) using GCP-native toolstack.
Working closely with the stakeholders & designed end to end life cycle on big data, data engineering, data management, data governance solutions and ensuring architecture meets the business requirements and building highly scalable, robust & fault-tolerant systems. Branching strategies and Version Control using GitHub. Worked with building language models, machine learning and AI models leveraging industry tools, products, and Azure cognitive services.
Solved critical problems in large-scale Data Science, Big Data & Data Engineering, Data Analytics, Cloud, interoperability and Machine Learning Engineering, developing end-to-end edge solution architectures for cross-sector and regional use cases, enabling the successful deployment of edge solutions for various industries. DAG and Workflow orchestration using airflow/cloud composer. Technology-Stack suggestion based on 360 Degree Analysis.
Built and deployed scalable machine learning models using cloud-based services such as AWS, GCP and Azure. Strong understanding of deep learning algorithms, statistics, and recommendation system. Comprehensive understanding of state-of-the-art language models including Generative AI, LLMs, etc. Agile software Development concept. Involved aiding customers and strategize their Generative AI initiatives.
Worked as a Data/ Big Data Architect with skills in supervising activities like designing solutions as per client needs, providing pre-sales support, migrating applications to the cloud, enabling sales, developing tools, ensuring on-time delivery, implementing process automation & engineering, and so on. Code refactorization & coding best practices implementation as per industry standard. Implementing MLOps practices on project and follow the set MLOps practices.
Management of Hadoop cluster and cloud platforms like Snowflake. Experience with building stream-processing systems, using solutions like Storm and Spark-Streaming. Experience with various messaging systems, like Kafka and RabbitMQ. Working on Reporting and Visualization tools like Qlick, Tableau, Power BI, Cloud-native Architecture etc., Competency using MLOps and AIOps tools such as cnvrg.io, mlfow, and Domino
Responsible for understanding business problems, building analytical solutions, client management, project delivery and inspiring others along with leading and optimizing investment in people, data, and technology. Support the ML models throughout the E2E MLOps lifecycle from development to maintenance. Knowledge sharing session with team for specific ML Ops topics. Guide and Mentor team members for MLOps framework development
Data Analytics Strategy Developed and implemented a comprehensive strategy aligned with the business objectives to foster growth and success in the analytics domain. Micro Services Architecture and framework Development concept. Responsible to identify and managing asset reliability risk and able to reduce it. Building and customizing and fine-tuning AI models including LLM models via OpenAI, Bert for rapid PoCs. Responsible to formulate business development strategies for Generative AI Practice. Created differentiated solution & Services offerings and translate into revenue growth.
Independently managed the full life cycle of data analysis and model development, including detailed EDA, analytic s solution framework design, dateset development, model creation, and validation, driving innovation and delivering impactful solutions. Responsible for P&L for Big Data Engagements. Managing Alliance with AWS and Databricks for Data Analytics offerings.
Built and deployed ML pipelines, ensuring efficient software and AIML development, as well as data analysis, experimentation, operationalization, model training, and model tuning, leading to improved efficiency and effectiveness of processes. Responsible for providing both business and technical services for a range of customer-facing consulting activities that specialize in Generative AI. Architect AI solutions and managed the delivery of highly technical analytics use cases.
Responsible for design, development, implementation, operation improvement and debug BI & Data Analytics, Quantitative Analytics environments on premise / on Cloud Management Platform. Deep understanding of data strategies, platforms, and data analytics. Management of Hadoop cluster and cloud platforms like Snowflake.
Consulted with clients on foundational Cloud, Data, and AI/ML requirements, building PoCs to demonstrate understanding and knowledge of AI/ML tools, ensuring client satisfaction. Reviewed projects PR and PBIs and suggestion for improvement
Collaborated closely with machine learning engineers and researchers to accelerate AI/ML development for use-case deployment, optimizing resource utilization and project timelines. Collaborating with Data Scientists, Data Engineers, Platform Engineers and Tech Expertise to support the analytic consumption needs.
Spearheaded the design and development of AI/ ML-powered full-stack applications using cloud-native services, accelerating clients' path to value and enhancing business outcomes. Collaborated with technical teams like Data Science Lead, Data Scientists, Data Engineers and Platform owners. Worked on Analytic tools dbt, atscale, neo4j, Atlassia, etc.,
Fostered a culture of knowledge sharing and continuous learning within the AI/ML community of practice by mentoring peers and apprentices. Knowledge sharing with the broader analytics team and stakeholders. Operationalize the ML and AI models, entails model management and monitoring too. Recommend innovative ways to automate the MLOps pipelines on GCP and set standards that would ensure repeated success.
Worked as Pre-Sales Consultant, Technical Architects and Practice Leaders to ensure that we designed the right solutions for our customers. Ability to communicate the accomplishments, failures, and risks in timely manner.
Owns the proposal and Statement of Work (SoW) overall and engages pre-sales consultant for more complex content related to the specific practice. Align on the key priorities and focus areas. Capability is leveraged to fuel advanced Analytical solutions, Machine Learning and Deep Learning.
Effectively communicated complex data and ML problems and solutions to non-technical users, ensuring a clear understanding of project objectives and deliverables. Research and operationalize technology and processes necessary to scale ML Ops.
Independently managed the full life cycle of data analysis and model development, including detailed EDA, analytic s solution framework design, dateset development, model creation, and validation, driving innovation and delivering impactful solutions.
Responsible for implementing and enhancing community of practice to determine the best practices, standards, and MLOps frameworks to efficiently delivery enterprise data solutions
Expertly manipulated and integrated big data and different data types, including videos, images, documents, and structured databases, to create comprehensive data solutions. MLOps pipeline improvement plan and suggestion. Enhanced the performance of the models and automates the production pipelines to gain efficiency.
Managing and delivering on all delivery aspects of the Data Stack including Development, Operations and Analytics. Guiding a team of data engineers, database administrators and analysts including creating technical roadmaps, and recommending strategies for data pipelines/integration. Ability to research and recommend MLOps best practices on new technologies, platforms, and services. Collaborated with clients to identify opportunities for AI integration, providing expert guidance and building strong, long-term relationships.
Successfully created an 18-node Hadoop cluster environment using Cloudera CDH4 version, enabling efficient data processing and analysis, leading to improved business insights.
Implemented flume for loading logs into HDFS, improving data collection and storage capabilities, ensuring seamless data access and retrieval. Build, Enhance, optimized Data Pipelines using Reusable frameworks to support data need for the analytics and Business team using Python and PySpark
Managing the AI practice resources within our company. Involved in client-facing responsibilities, excellent communication skills, and a strong focus on business development through crafting and presenting new proposals for prospective clients.
Developed queries in Pig Scripts for data analysis, enhancing the efficiency and accuracy of data processing, driving data-driven decision-making processes. Prepared Low-Level Design (LLD) for integration solutions.
Participated in pre-sales activities, including client presentations, workshops, and demonstrations to showcase the capabilities of our AI solutions. Experience designing and developing Data Model, Data Mart, Data Mesh, Data Governance, Data Mining and Data Warehousing. Expertise in data security / Infrastructure Security and integration architecture.
Implemented the Map Reduce program for converting log files to CSV format. Involved in transfer of data from PostgreSQL tables into HDFS and Hive using Sqoop. Involved in creating Hive tables, and then applied HiveQL on those tables for data validation.
Demonstrated experience in business development, including proposal creation and client presentations. Proven track record of successfully delivering Big data and AI projects and solutions.
Developed and Tested MapReduce Jobs in Java to analyze the data. Implemented the hive partitions, hive joins. Involved in Cluster maintenance, Cluster Monitoring and Troubleshooting. Involved in managing and reviewing data backups and log files.
Led the successful implementation of Map Reduce programs for converting log files to CSV format, streamlining data transformation processes and enhancing data organization.
Managing the Big data and AI practice resources within our company. Involved in client-facing responsibilities, excellent communication skills, and a strong focus on business development through crafting and presenting new proposals for prospective clients. Expertise in data security / Infrastructure Security and integration architecture.
Collaborated with Data Analysts, Data Engineers, DBAs, cross-functional teams, and business stakeholders to tackle everyday problems in an innovative way. Providing technical expertise to the team as they developing, implementing, and operate data engineering solutions. Prepared Low-Level Design (LLD) for integration solutions.
Very clear about the data flows, data architecture, ETL/ELT and processing of structured and unstructured data. Responsible to maintain Security and Data Privacy, Data Security and Compliance. Handled the project end to end, ensure positive team environment and identify improvement. Strong understanding of security principles, including Data Tokenization.
Involved in the implementation of flume for loading logs into HDFS. Involved in HBase configuration, HBase java API. Implemented Queries in Pig Scripts for analyzing the data and Store the log file into HDFS. Loading data into Hive table.
Working in data analytics and technology exposure to end to end data solution architecture/ Data Strategy/Data Mining/process architecture/frameworks/Data Governance/Data Quality/Data security/MDM/Visualization/AI/ML. Created the 18 node Hadoop cluster environment by using Cloudera CDH4 version
M.Tech Computer Science (2005) 2016: PG Diploma in Data Science, Artificial Intelligence, and Machine Learning from International Institute of Information Technology, Bengaluru 2023 : Indian Institute of Management- Lucknow - Senior Leadership Program (Pursuing)