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Key Responsibilities : ( Data Developer Python, Spark)

Exp : 2 to 9 Yrs 

Development of data platforms, integration frameworks, processes, and code.

Develop and deliver APIs in Python or Scala for Business Intelligence applications build using a range of web languages

Develop comprehensive automated tests for features via end-to-end integration tests, performance tests, acceptance tests and unit tests.

Elaborate stories in a collaborative agile environment (SCRUM or Kanban)

Familiarity with cloud platforms like GCP, AWS or Azure.

Experience with large data volumes.

Familiarity with writing rest-based services.

Experience with distributed processing and systems

Experience with Hadoop / Spark toolsets

Experience with relational database management systems (RDBMS)

Experience with Data Flow development

Knowledge of Agile and associated development techniques including:

n 

• Mandatory - Hands on experience in Python and PySpark.

 

• Build pySpark applications using Spark Dataframes in Python using Jupyter notebook and PyCharm(IDE).

 

• Worked on optimizing spark jobs that processes huge volumes of data.

 

• Hands on experience in version control tools like Git.

 

• Worked on Amazon’s Analytics services like Amazon EMR, Lambda function etc

 

• Worked on Amazon’s Compute services like Amazon Lambda, Amazon EC2 and Amazon’s Storage service like S3 and few other services like SNS.

 

• Experience/knowledge of bash/shell scripting will be a plus.

 

• Experience in working with fixed width, delimited , multi record file formats etc.

 

• Hands on experience in tools like Jenkins to build, test and deploy the applications

 

• Awareness of Devops concepts and be able to work in an automated release pipeline environment.

 

• Excellent debugging skills.

Responsibilities
● Create and maintain optimal data pipeline architecture.
● Assemble large, complex data sets that meet functional / non-functional
business requirements.
● Building and optimizing ‘big data’ data pipelines, architectures and data sets.
● Maintain, organize & automate data processes for various use cases.
● Identifying trends, doing follow-up analysis, preparing visualizations.
● Creating daily, weekly and monthly reports of product KPIs.
● Create informative, actionable and repeatable reporting that highlights
relevant business trends and opportunities for improvement.

Required Skills And Experience:
● 2-5 years of work experience in data analytics- including analyzing large data sets.
● BTech in Mathematics/Computer Science
● Strong analytical, quantitative and data interpretation skills.
● Hands-on experience with Python, Apache Spark, Hadoop, NoSQL
databases(MongoDB preferred), Linux is a must.
● Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
● Experience with Google Cloud Data Analytics Products such as BigQuery, Dataflow, Dataproc etc. (or similar cloud-based platforms).
● Experience working within a Linux computing environment, and use of
command-line tools including knowledge of shell/Python scripting for
automating common tasks.
● Previous experience working at startups and/or in fast-paced environments.
● Previous experience as a data engineer or in a similar role.

• We are looking for : Data engineer
• Sprak
• Scala
• Hadoop

Exp - 5 to 9 years
N.p - 15 days to 30 Days
Location : Bangalore / Noida

Data Scientist

Requirements

● B.Tech/Masters in Mathematics, Statistics, Computer Science or another
quantitative field
● 2-3+ years of work experience in ML domain ( 2-5 years experience )
● Hands-on coding experience in Python
● Experience in machine learning techniques such as Regression, Classification,
Predictive modeling, Clustering, Deep Learning stack, NLP
● Working knowledge of Tensorflow/PyTorch

Optional Add-ons-

● Experience with distributed computing frameworks: Map/Reduce, Hadoop, Spark
etc.
● Experience with databases: MongoDB

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!

Responsibilities:

• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world.
• Verifying data quality, and/or ensuring it via data cleaning.
• Able to adapt and work fast in producing the output which upgrades the decision making of stakeholders using ML.
• To design and develop Machine Learning systems and schemes. 
• To perform statistical analysis and fine-tune models using test results.
• To train and retrain ML systems and models as and when necessary. 
• To deploy ML models in production and maintain the cost of cloud infrastructure.
• To develop Machine Learning apps according to client and data scientist requirements.
• To analyze the problem-solving capabilities and use-cases of ML algorithms and rank them by how successful they are in meeting the objective.

Technical Knowledge:

• Worked with real time problems, solved them using ML and deep learning models deployed in real time and should have some awesome projects under his belt to showcase. 
• Proficiency in Python and experience with working with Jupyter Framework, Google collab and cloud hosted notebooks such as AWS sagemaker, DataBricks etc.
• Proficiency in working with libraries Sklearn, Tensorflow, Open CV2, Pyspark,  Pandas, Numpy and related libraries.
• Expert in visualising and manipulating complex datasets.
• Proficiency in working with visualisation libraries such as seaborn, plotly, matplotlib etc.
• Proficiency in Linear Algebra, statistics and probability required for Machine Learning.
• Proficiency in ML Based algorithms for example, Gradient boosting, stacked Machine learning, classification algorithms and deep learning algorithms. Need to have experience in hypertuning various models and comparing the results of algorithm performance.
• Big data Technologies such as Hadoop stack and Spark. 
• Basic use of clouds (VM’s example EC2).
• Brownie points for Kubernetes and Task Queues.      
• Strong written and verbal communications.
• Experience working in an Agile environment.

What you will be doing:

As a part of the Global Credit Risk and Data Analytics team, this person will be responsible for carrying out analytical initiatives which will be as follows: -

• Dive into the data and identify patterns
• Development of end-to-end Credit models and credit policy for our existing credit products
• Leverage alternate data to develop best-in-class underwriting models
• Working on Big Data to develop risk analytical solutions
• Development of Fraud models and fraud rule engine
• Collaborate with various stakeholders (e.g. tech, product) to understand and design best solutions which can be implemented
• Working on cutting-edge techniques e.g. machine learning and deep learning models

Example of projects done in past:

• Lazypay Credit Risk model using CatBoost modelling technique ; end-to-end pipeline for feature engineering and model deployment in production using Python
• Fraud model development, deployment and rules for EMEA region

 

Basic Requirements:

• 1-3 years of work experience as a Data scientist (in Credit domain)
• 2016 or 2017 batch from a premium college (e.g B.Tech. from IITs, NITs, Economics from DSE/ISI etc)
• Strong problem solving and understand and execute complex analysis
• Experience in at least one of the languages - R/Python/SAS and SQL
• Experience in in Credit industry (Fintech/bank)
• Familiarity with the best practices of Data Science

 

Add-on Skills : 

• Experience in working with big data
• Solid coding practices
• Passion for building new tools/algorithms
• Experience in developing Machine Learning models

Job Description : Role : Analytics Scientist - Risk Analytics Experience Range : 1 to 4 Years Job Location : Noida Key responsibilities include •Building models to predict risk and other key metrics •Coming up with data driven solutions to control risk •Finding opportunities to acquire more customers by modifying/optimizing existing rules •Doing periodic upgrades of the underwriting strategy based on business requirements •Evaluating 3rd party solutions for predicting/controlling risk of the portfolio •Running periodic controlled tests to optimize underwriting •Monitoring key portfolio metrics and take data driven actions based on the performance Business Knowledge: Develop an understanding of the domain/function. Manage business process (es) in the work area. The individual is expected to develop domain expertise in his/her work area. Teamwork: Develop cross site relationships to enhance leverage of ideas. Set and manage partner expectations. Drive implementation of projects with Engineering team while partnering seamlessly with cross site team members Communication: Responsibly perform end to end project communication across the various levels in the organization. Candidate Specification: Skills: • Knowledge of analytical tool - R Language or Python • Established competency in Predictive Analytics (Logistic & Regression) • Experience in handling complex data sources •Dexterity with MySQL, MS Excel is good to have •Strong Analytical aptitude and logical reasoning ability •Strong presentation and communication skills Preferred: •1 - 3 years of experience in Financial Services/Analytics Industry •Understanding of the financial services business • Experience in working on advanced machine learning techniques If interested, please send your updated profile in word format with below details for further discussion at the earliest. 1. Current Company 2. Current Designation 3. Total Experience 4. Current CTC( Fixed & Variable) 5. Expected CTC 6. Notice Period 7. Current Location 8. Reason for Change 9. Availability for face to face interview on weekdays 10.Education Degreef the financial services business Thanks & Regards, Hema Talent Socio

Location: Gurgaon Role: • The person will be part of data science team. This person will be working on a close basis with the business analysts and the technology team to deliver the Data Science portion of the project and product. • Data Science contribution to a project can range between 30% to 80%. • Day to Day activities will include data exploration to solve a specific problem, researching of methods to be applied as solution, setting up ML process to be applied in context of a specific engagement/ requirement, contributing to building a DS platform, coding the solution, interacting with client on explanations, integration the DS solution with the technology solution, data cleaning and structuring etc. • Nature of work will depend on stage of a specific engagement, available engagements and individual skill At least 2-6 years of experience in: • Machine Learning (including deep learning methods): Algorithm design, analysis and development and performance improvement o Strong understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering, classification, regression techniques, and recommendation (collaborative filtering) algorithms o Time Series Analysis o Optimization techniques and work experience with solvers for MILP and global optimization. • Data Science o Good experience in exploratory data analysis and feature design & development o Experience of applying and evaluating ML algorithms to practical predictive modeling scenarios in various verticals including (but not limited to) FMCG, Media, E-commerce and Hospitality. • Proficient with programming in Python (must have) & PySpark (good to have). Parallel ML algorithms design and development and usage for maximal performance on multi-core, distributed and/or GPU architectures. • Must be able to write a production ready code with reusable components and integration into data science platform. • Strong inclination to write structured code as per prevailing coding standards and best practices. • Ability to design a data science architecture for repeatability of solutions • Preparedness to manage whole cycle from data preparation to algorithm design to client presentation at individual level. • Comfort in working on AWS including managing data science AWS servers • Team player and good communication and interpersonal skills • Good experience in Natural Language Processing and its applications (Good to Have)

About the job: - You will work with data scientists to architect, code and deploy ML models - You will solve problems of storing and analyzing large scale data in milliseconds - architect and develop data processing and warehouse systems - You will code, drink, breathe and live python, sklearn and pandas. It’s good to have experience in these but not a necessity - as long as you’re super comfortable in a language of your choice. - You will develop tools and products that provide analysts ready access to the data About you: - Strong CS fundamentals - You have strong experience in working with production environments - You write code that is clean, readable and tested - Instead of doing it second time, you automate it - You have worked with some of the commonly used databases and computing frameworks (Psql, S3, Hadoop, Hive, Presto, Spark, etc) - It will be great if you have one of the following to share - a kaggle or a github profile - You are an expert in one or more programming languages (Python preferred). Also good to have experience with python-based application development and data science libraries. - Ideally, you have 2+ years of experience in tech and/or data. - Degree in CS/Maths from Tier-1 institutes.