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About Vedantu
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Work Timing: 5 Days A Week
Responsibilities include:
• Ensure right stakeholders gets right information at right time
• Requirement gathering with stakeholders to understand their data requirement
• Creating and deploying reports
• Participate actively in datamarts design discussions
• Work on both RDBMS as well as Big Data for designing BI Solutions
• Write code (queries/procedures) in SQL / Hive / Drill that is both functional and elegant,
following appropriate design patterns
• Design and plan BI solutions to automate regular reporting
• Debugging, monitoring and troubleshooting BI solutions
• Creating and deploying datamarts
• Writing relational and multidimensional database queries
• Integrate heterogeneous data sources into BI solutions
• Ensure Data Integrity of data flowing from heterogeneous data sources into BI solutions.
Minimum Job Qualifications:
• BE/B.Tech in Computer Science/IT from Top Colleges
• 1-5 years of experience in Datawarehousing and SQL
• Excellent Analytical Knowledge
• Excellent technical as well as communication skills
• Attention to even the smallest detail is mandatory
• Knowledge of SQL query writing and performance tuning
• Knowledge of Big Data technologies like Apache Hadoop, Apache Hive, Apache Drill
• Knowledge of fundamentals of Business Intelligence
• In-depth knowledge of RDBMS systems, Datawarehousing and Datamarts
• Smart, motivated and team oriented
Desirable Requirements
• Sound knowledge of software development in Programming (preferably Java )
• Knowledge of the software development lifecycle (SDLC) and models
Role: Head of Analytics
Location: Bangalore (Full time)
ABOUT QRATA:
Qrata matches top talent with global career opportunities from the world’s leading digital companies including some of the world’s fastest growing startups using Qrata’s talent marketplaces. To sign-up, please visit Qrata Talent Sign-Up
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.
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Job Description
We are looking for an experienced engineer with superb technical skills. Primarily be responsible for architecting and building large scale data pipelines that delivers AI and Analytical solutions to our customers. The right candidate will enthusiastically take ownership in developing and managing a continuously improving, robust, scalable software solutions.
Although your primary responsibilities will be around back-end work, we prize individuals who are willing to step in and contribute to other areas including automation, tooling, and management applications. Experience with or desire to learn Machine Learning a plus.
Skills
- Bachelors/Masters/Phd in CS or equivalent industry experience
- Demonstrated expertise of building and shipping cloud native applications
- 5+ years of industry experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka Streams, Py Spark, and streaming databases like druid or equivalent like Hive
- Strong industry expertise with containerization technologies including kubernetes (EKS/AKS), Kubeflow
- Experience with cloud platform services such as AWS, Azure or GCP especially with EKS, Managed Kafka
- 5+ Industry experience in python
- Experience with popular modern web frameworks such as Spring boot, Play framework, or Django
- Experience with scripting languages. Python experience highly desirable. Experience in API development using Swagger
- Implementing automated testing platforms and unit tests
- Proficient understanding of code versioning tools, such as Git
- Familiarity with continuous integration, Jenkins
Responsibilities
- Architect, Design and Implement Large scale data processing pipelines using Kafka Streams, PySpark, Fluentd and Druid
- Create custom Operators for Kubernetes, Kubeflow
- Develop data ingestion processes and ETLs
- Assist in dev ops operations
- Design and Implement APIs
- Identify performance bottlenecks and bugs, and devise solutions to these problems
- Help maintain code quality, organization, and documentation
- Communicate with stakeholders regarding various aspects of solution.
- Mentor team members on best practices
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Qualifications
B.Tech/M.Tech
Percentage 70% and above
2018 & 2019 passouts
At least 3 POC Implementations should have done
Premium Institutes passouts are more preferrable
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- Proficient in R and Python
- Work experience 1+ years with at least 6 months working with Python
- Prior experience with building ML models
- Prior experience with SQL
- Knowledge of statistical techniques
- Experience with working on Spatial Data will be an added advantage
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------------------------
Solve problems in speech and NLP domain using advanced Deep learning and Machine Learning techniques. Few examples of the problems are -
* Limited resource Speaker Diarization on mono-channel recordings in noisy environment.
* Speech Enhancement to improve accuracy of downstream speech analytics tasks.
* Automated Speech Recognition for accent heavy audio with a noisy background.
* Speech analytic tasks, which include: emotions, empathy, keyword extraction.
* Text analytic tasks, which include: topic modeling, entity and intent extraction, opinion mining, text classification, and sentiment detection on multilingual data.
A typical day at work
-----------------------------
You will work closely with the product team to own a business problem. You will then model the business problem into a Machine Learning problem. Next you will do literature review to identify approaches to solve the problem. Test these approaches, identify the best approach, add your own insights to improve the performance and ship that to production!
What should you know?
---------------------------------
* Solid understanding of Classical Machine Learning and Deep Learning concepts and algorithms.
* Experience with literature review either in academia or industry.
* Proficiency in at least one programming language such as Python, C, C++, Java, etc.
* Proficiency in Machine Learning tools such as TensorFlow, Keras, Caffe, Torch/PyTorch or Theano.
* Advanced degree in Computer Science, Electrical Engineering, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics
Why DeepAffects?
--------------------------
* You’ll learn insanely fast here.
* Esops and competitive compensation.
* Opportunity and encouragement for publishing research at top conferences, paid trips to attend workshop and conferences where you have published.
* Independent work, flexible timings and sense of ownership of your work.
* Mentorship from distinguished researchers and professors.
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