Automation testing

Skills and competencies:

Required:

·        Strong analytical skills in conducting sophisticated statistical analysis using bureau/vendor data, customer performance

Data and macro-economic data to solve business problems.

·        Working experience in languages PySpark & Scala to develop code to validate and implement models and codes in

Credit Risk/Banking

·        Experience with distributed systems such as Hadoop/MapReduce, Spark, streaming data processing, cloud architecture.

• Familiarity with machine learning frameworks and libraries (like scikit-learn, SparkML, tensorflow, pytorch etc.
• Experience in systems integration, web services, batch processing
• Experience in migrating codes to PySpark/Scala is big Plus
• The ability to act as liaison conveying information needs of the business to IT and data constraints to the business

applies equal conveyance regarding business strategy and IT strategy, business processes and work flow

·        Flexibility in approach and thought process

·        Attitude to learn and comprehend the periodical changes in the regulatory requirement as per FED

Strong Data Scientist/Machine Learnings/ AI Engineer Profile

Mandatory (Experience 1) – Must have 2+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models

Mandatory (Experience 2) – Must have strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.

Mandatory (Experience 3) – Must have hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models

Mandatory (Experience 4) – Must have strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text

Mandatory (Experience 5) – Must have experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments

Mandatory (Company) – Must be from product companies, Avoid candidates from financial domains (e.g., JPMorgan, banks, fintech)

We are seeking enthusiastic individuals to join our team as Customer Care Executives for both Voice and Sales processes. As a Customer Care Executive, you will be responsible for addressing customer inquiries, resolving issues, and promoting our products/services to potential customers.

**Qualifications:**

- Minimum educational qualification: 12th pass.

- Age between 18 to 30 years.

- Excellent communication skills in English and Hindi

- Ability to handle customer queries and provide appropriate solutions.

- Prior experience in customer service or sales is preferred but not mandatory.

**Responsibilities:**

- Handle inbound/outbound calls professionally and provide information about products/services.

- Identify customer needs, clarify information, and close sales.

- Maintain a high level of customer satisfaction through effective problem-solving.

- Achieve sales targets and goals as set by the company

Responsibilities

• Plan, develop and implement large-scale projects from conception to completion.
• Interface with clients and gather business requirements and objectives.
• Translate clients’ business requirements and objectives into technical applications and solutions.
• Understand and evaluate complex data models.
• Design, develop and implement new integration.
• Execute system development and maintenance activities.
• Develop solutions to improvise performance and scalability of systems.
• Mentor junior and mid-level engineers.

Minimum Requirements

• 3-5 years of relevant experience, working in Java related technologies.
• A Good Engineering or Masters degree from a reputed university
• Should have strong technical skills with a good grasp of OO concepts and design patterns

• Good knowledge of SQL database ( MySQL, Oracle, etc )
• Good understanding of frameworks like Spring, Hibernate, etc.
• Good understanding of spring boot and microservices.
• Exposure to AWS services - S3, SQS, Lambda, DynamoDB, API Gateway, etc.

Good to have

• Knowledge of No-SQL DBs like mongo, dynamoDB, etc.
• Knowledge of message brokers/queuing services like SQL, rabbitMQ, Kafka, etc.