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We are seeking a skilled AWS ETL/ELT Data Architect with a specialization in MongoDB to join our team. The ideal candidate will possess comprehensive knowledge and hands-on experience
in designing, implementing, and managing ETL/ELT processes within AWS while also demonstrating proficiency in MongoDB database management.
This role requires expertise in data architecture, AWS services, and MongoDB to optimize data solutions effectively.
Responsibilities:
● Design, architect, and implement ETL/ELT processes within AWS, integrating data from various sources into data lakes or warehouses, and utilising MongoDB as part of the data ecosystem.
● Collaborate cross-functionally to assess data requirements, analyze sources, and strategize effective data integration within AWS environments, considering MongoDB's role in the architecture.
● Construct scalable and high-performance data pipelines within AWS while integrating MongoDB for optimal data storage, retrieval, and manipulation.
● Develop comprehensive documentation covering data architecture, flows, and the interplay between AWS services, MongoDB, and ETL/ELT processes from scratch.
● Perform thorough data profiling, validation, and troubleshooting, ensuring data accuracy, consistency, and integrity in conjunction with MongoDB management.
● Stay updated with AWS and MongoDB best practices, emerging technologies, and industry trends to propose innovative data solutions and implementations.
● Provide mentorship to junior team members and foster collaboration with stakeholders to deliver robust data solutions.
● Analyze data issues, identify and articulate the business impact of data problems
● Perform code reviews and ensure that all solutions are aligned with pre-defined architectural standards, guidelines, and best practices, and meet quality standards
Qualifications:
● Bachelor's or Master’s degree in Computer Science, Information Technology, or related field.
● Minimum 5 years of hands-on experience in ETL/ELT development, data architecture, or similar roles.
● Having implemented more than a minimum of 3-4 live projects in a similar field would be desirable.
● Expertise in designing and implementing AWS-based ETL/ELT processes using tools like AWS Glue, AWS Data Pipeline, etc.
● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypothesis through theoretical and empirical approaches.
● Productize proven or working models into production quality code.
● Collaborate with product management, marketing and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision makers.
● File patents for innovative solutions that add to company's IP portfolio
Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/PhD in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes (only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Expertise in Python programming language and fluency in analytical tools
such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis
● Strong communication and collaboration skills.
Role: Head of Analytics
Location: Bangalore (Full time)
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ABOUT THE COMPANY WE ARE HIRING FOR:
Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.
POSITION OVERVIEW
We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.
Responsibilities:
1. Develop and implement Analytics Strategy:
o Define the analytics roadmap for the credit card business, aligning it with overall
business objectives.
o Identify key performance indicators (KPIs) and metrics to track the performance
of the credit card business.
o Collaborate with senior management and cross-functional teams to prioritize and
execute analytics initiatives. 2. Lead Data Analysis and Insights:
o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.
o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.
o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.
o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.
3. Drive Data Governance and Quality:
o Oversee data governance initiatives, ensuring data accuracy, consistency, and
integrity across relevant systems and platforms.
o Collaborate with IT teams to optimize data collection, integration, and storage
processes to support advanced analytics capabilities.
o Establish and enforce data privacy and security protocols to comply with
regulatory requirements.
4. Team Leadership and Collaboration:
o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.
o Provide guidance and mentorship to the team, promoting professional growth and development.
o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.
5. Stay Updated on Industry Trends:
o Keep abreast of emerging trends, techniques, and technologies in analytics, credit
card business, and the financial industry.
o Leverage industry best practices to drive innovation and continuous improvement
in analytics methodologies and tools.
Qualifications:
Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.
Proven experience (7+ years) in leading analytics teams in the credit card industry.
Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.
Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.
Experience with analytics tools such as SAS, SPSS, or Tableau.
Excellent leadership and team management skills, with a track record of building and developing high-performing teams.
Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.
Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience.
Job Responsibilities
- Design machine learning systems
- Research and implement appropriate ML algorithms and tools
- Develop machine learning applications according to requirements
- Select appropriate datasets and data representation methods
- Run machine learning tests and experiments
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
Requirements for the Job
- Bachelor’s/Master's/PhD in Computer Science, Mathematics, Statistics or equivalent field andmust have a minimum of 2 years of overall experience in tier one colleges
- Minimum 1 year of experience working as a Data Scientist in deploying ML at scale in production
- Experience in machine learning techniques (e.g. NLP, Computer Vision, BERT, LSTM etc..) andframeworks (e.g. TensorFlow, PyTorch, Scikit-learn, etc.)
- Working knowledge in deployment of Python systems (using Flask, Tensorflow Serving)
- Previous experience in following areas will be preferred: Natural Language Processing(NLP) - Using LSTM and BERT; chatbots or dialogue systems, machine translation, comprehension of text, text summarization.
- Computer Vision - Deep Neural Networks/CNNs for object detection and image classification, transfer learning pipeline and object detection/instance segmentation (Mask R-CNN, Yolo, SSD).
4-6 years of total experience in data warehousing and business intelligence
3+ years of solid Power BI experience (Power Query, M-Query, DAX, Aggregates)
2 years’ experience building Power BI using cloud data (Snowflake, Azure Synapse, SQL DB, data lake)
Strong experience building visually appealing UI/UX in Power BI
Understand how to design Power BI solutions for performance (composite models, incremental refresh, analysis services)
Experience building Power BI using large data in direct query mode
Expert SQL background (query building, stored procedure, optimizing performance)
• Help build a Data Science team which will be engaged in researching, designing,
implementing, and deploying full-stack scalable data analytics vision and machine learning
solutions to challenge various business issues.
• Modelling complex algorithms, discovering insights and identifying business
opportunities through the use of algorithmic, statistical, visualization, and mining techniques
• Translates business requirements into quick prototypes and enable the
development of big data capabilities driving business outcomes
• Responsible for data governance and defining data collection and collation
guidelines.
• Must be able to advice, guide and train other junior data engineers in their job.
Must Have:
• 4+ experience in a leadership role as a Data Scientist
• Preferably from retail, Manufacturing, Healthcare industry(not mandatory)
• Willing to work from scratch and build up a team of Data Scientists
• Open for taking up the challenges with end to end ownership
• Confident with excellent communication skills along with a good decision maker
2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research
GREETINGS FROM CODEMANTRA !!!
EXCELLENT OPPORTUNITY FOR DATA SCIENCE/AI AND ML ARCHITECT !!!
Skills and Qualifications
*Strong Hands-on experience in Python Programming
*** Working experience with Computer Vision models - Object Detection Model, Image Classification
* Good experience in feature extraction, feature selection techniques and transfer learning
* Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
* Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
* Good experience in exploratory data analysis, data visualisation, and other data pre-processing techniques.
* Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe Good knowledge in statistics, distribution of data and in supervised and unsupervised machine learning algorithms.
* Exposure to OpenCV Familiarity with GPUs + CUDA Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
* We are looking for a candidate with 9+ years of relevant experience , who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools: *Experience with big data tools: Hadoop, Spark, Kafka, etc.
*Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
*Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.
Responsibilities
*Selecting features, building and optimizing classifiers using machine learning techniques
*Data mining using state-of-the-art methods
*Enhancing data collection procedures to include information that is relevant for building analytic systems
*Processing, cleansing, and verifying the integrity of data used for analysis
*Creating automated anomaly detection systems and constant tracking of its performance
*Assemble large, complex data sets that meet functional / non-functional business requirements.
*Secure and manage when needed GPU cluster resources for events
*Write comprehensive internal feedback reports and find opportunities for improvements
*Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model
Regards
Ranjith PRML ARCHITECT
Job Overview
We are looking for a ML Architect to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems integrated with our products. They must have strong experience using variety of data mining and data analysis methods, building and implementing models, using/creating algorithm’s and creating/running simulations. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes. Automating to identify the textual data with their properties and structure form various type of document.
Responsibilities
- Selecting features, building and optimizing classifiers using machine learning techniques
- Data mining using state-of-the-art methods
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
- Creating automated anomaly detection systems and constant tracking of its performance
- Assemble large, complex data sets that meet functional / non-functional business requirements.
- Secure and manage when needed GPU cluster resources for events
- Write comprehensive internal feedback reports and find opportunities for improvements
- Manage GPU instances/machines to increase the performance and efficiency of the ML/DL model.
Skills and Qualifications
- Strong Hands-on experience in Python Programming
- Working experience with Computer Vision models - Object Detection Model, Image Classification
- Good experience in feature extraction, feature selection techniques and transfer learning
- Working Experience in building deep learning NLP Models for text classification, image analytics-CNN,RNN,LSTM.
- Working Experience in any of the AWS/GCP cloud platforms, exposure in fetching data from various sources.
- Good experience in exploratory data analysis, data visualisation, and other data preprocessing techniques.
- Knowledge in any one of the DL frameworks like Tensorflow, Pytorch, Keras, Caffe
- Good knowledge in statistics,distribution of data and in supervised and unsupervised machine learning algorithms.
- Exposure to OpenCV Familiarity with GPUs + CUDA
- Experience with NVIDIA software for cluster management and provisioning such as nvsm, dcgm and DeepOps.
- We are looking for a candidate with 14+ years of experience, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with AWS cloud services: EC2, RDS, AWS-Sagemaker(Added advantage)
- Experience with object-oriented/object function scripting languages in any: Python, Java, C++, Scala, etc.