AWS Data Engineer (Contractual)

Data Scientist-

We are looking for an experienced Data Scientists to join our engineering team and

help us enhance our mobile application with data. In this role, we're looking for

people who are passionate about developing ML/AI in various domains that solves

enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering

problems.

As one of the earliest members in engineering, you will have the flexibility to design

the models and architecture from ground up. As any early-stage start-up, we expect

you to be comfortable wearing various hats, and be proactive contributor in building

something truly remarkable.

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

• Act as primary day-to-day contact on analytics to agency-client leads
• Develop bespoke analytics proposals for presentation to agencies & clients, for delivery within the teams
• Ensure delivery of projects and services across the analytics team meets our stakeholder requirements (time, quality, cost)
• Hands on platforms to perform data pre-processing that involves data transformation as well as data cleaning
  
• Ensure data quality and integrity
  
• Interpret and analyse data problems
  
• Build analytic systems and predictive models
  
• Increasing the performance and accuracy of machine learning algorithms through fine-tuning and further
  
• Visualize data and create reports
  
• Experiment with new models and techniques
  
• Align data projects with organizational goals

• Min 6 - 7 years’ experience working in Data Science
• Prior experience as a Data Scientist within a digital media is desirable
• Solid understanding of machine learning
• A degree in a quantitative field (e.g. economics, computer science, mathematics, statistics, engineering, physics, etc.)
• Experience with SQL/ Big Query/GMP tech stack / Clean rooms such as ADH
• A knack for statistical analysis and predictive modelling
• Good knowledge of R, Python
• Experience with SQL, MYSQL, PostgreSQL databases
• Knowledge of data management and visualization techniques
• Hands-on experience on BI/Visual Analytics Tools like PowerBI or Tableau or Data Studio
• Evidence of technical comfort and good understanding of internet functionality desirable
• Analytical pedigree - evidence of having approached problems from a mathematical perspective and working through to a solution in a logical way
• Proactive and results-oriented
• A positive, can-do attitude with a thirst to continually learn new things
• An ability to work independently and collaboratively with a wide range of teams
• Excellent communication skills, both written and oral

• You're proficient in AI/Machine learning latest technologies  
• You're proficient in GPT-3 based algorithms 
• You have a passion for writing code as well as understanding and crafting the ways systems interact
• You believe in the benefits of agile processes and shipping code often
• You are pragmatic and work to coalesce requirements into reasonable solutions that provide value

• Deploy well-tested, maintainable and scalable software solutions
• Take end-to-end ownership of the technology stack and product 
• Collaborate with other engineers to architect scalable technical solutions
• Embrace and improve our standards and processes to reduce friction and unlock efficiency

• Minimum 1 years of relevant experience, in PySpark (mandatory)
• Hands on experience in development, test, deploy, maintain and improving data integration pipeline in AWS cloud environment is added plus 
• Ability to play lead role and independently manage 3-5 member of Pyspark development team 
• EMR ,Python and PYspark mandate.
• Knowledge and awareness working with AWS Cloud technologies like Apache Spark, , Glue, Kafka, Kinesis, and Lambda in S3, Redshift, RDS

Work Experience : 0-2 years

Responsibilities :

- Design and implement mathematical models for fundamental valuation of securities. The person will need to understand latest research in quantitative finance and implement the same.

- Design, back-testing and implementation of high-frequency trading strategies on international exchanges. Work as part of the market-making team to determine the signals and trading strategies to go live with.

- Conduct performance attribution of live portfolios.

Required Skills :

- Strong candidates should have 0-2 years of work experience and successful track record in quantitative analysis preferably in the capital markets domain.

- Post-Graduate degree in statistics, finance, mathematics, engineering (Computer Science preferred) or other quantitative or computational disciplines

- Experience in using some or all of the following packages: R, MATLAB, SPSS, CART, C# .Net, Python

- Good written and oral communication skills.

- Strong experience working both independently and in a team-oriented collaborative environment.

- Entrepreneurial, self-motivated individual - high energy, high activity levels - passion for working with an innovative, small but rapidly growing company.

Who Are We

A research-oriented company with expertise in computer vision and artificial intelligence, at its core, Orbo is a comprehensive platform of AI-based visual enhancement stack. This way, companies can find a suitable product as per their need where deep learning powered technology can automatically improve their Imagery.

ORBO's solutions are helping BFSI, beauty and personal care digital transformation and Ecommerce image retouching industries in multiple ways.

WHY US

• Join top AI company
• Grow with your best companions
• Continuous pursuit of excellence, equality, respect
• Competitive compensation and benefits

You'll be a part of the core team and will be working directly with the founders in building and iterating upon the core products that make cameras intelligent and images more informative.

To learn more about how we work, please check out

https://www.orbo.ai/.

Description:

We are looking for a computer vision engineer to lead our team in developing a factory floor analytics SaaS product. This would be a fast-paced role and the person will get an opportunity to develop an industrial grade solution from concept to deployment.

Responsibilities:

• Research and develop computer vision solutions for industries (BFSI, Beauty and personal care, E-commerce, Defence etc.)
• Lead a team of ML engineers in developing an industrial AI product from scratch
• Setup end-end Deep Learning pipeline for data ingestion, preparation, model training, validation and deployment
• Tune the models to achieve high accuracy rates and minimum latency
• Deploying developed computer vision models on edge devices after optimization to meet customer requirements

Requirements:

• Bachelor’s degree
• Understanding about depth and breadth of computer vision and deep learning algorithms.
• Experience in taking an AI product from scratch to commercial deployment.
• Experience in Image enhancement, object detection, image segmentation, image classification algorithms
• Experience in deployment with OpenVINO, ONNXruntime and TensorRT
• Experience in deploying computer vision solutions on edge devices such as Intel Movidius and Nvidia Jetson
• Experience with any machine/deep learning frameworks like Tensorflow, and PyTorch.
• Proficient understanding of code versioning tools, such as Git

Our perfect candidate is someone that:

• is proactive and an independent problem solver
• is a constant learner. We are a fast growing start-up. We want you to grow with us!
• is a team player and good communicator

What We Offer:

• You will have fun working with a fast-paced team on a product that can impact the business model of E-commerce and BFSI industries. As the team is small, you will easily be able to see a direct impact of what you build on our customers (Trust us - it is extremely fulfilling!)
• You will be in charge of what you build and be an integral part of the product development process
• Technical and financial growth!

Job Description - Sr Azure Data Engineer

Roles & Responsibilities:

1. Hands-on programming in C# / .Net,
2. Develop serverless applications using Azure Function Apps.
3. Writing complex SQL Queries, Stored procedures, and Views. 
4. Creating Data processing pipeline(s).
5. Develop / Manage large-scale Data Warehousing and Data processing solutions.
6. Provide clean, usable data and recommend data efficiency, quality, and data integrity.

Skills

1. Should have working experience on C# /.Net.
2. Proficient with writing SQL queries, Stored Procedures, and Views
3. Should have worked on Azure Cloud Stack.
4. Should have working experience ofin developing serverless code.
5. Must have MANDATORILY worked on Azure Data Factory.

Experience 

1. 4+ years of relevant experience

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 1+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor etc)
• strong quantitative and programming skills with a product-driven sensibility