Machine Learning Engineer

Qualifications :

• Minimum 2 years of .NET development experience (ASP.Net 3.5 or greater and C# 4 or greater).
• Good knowledge of MVC, Entity Framework, and Web API/WCF.
• ASP.NET Core knowledge is preferred.
• Creating APIs / Using third-party APIs
• Working knowledge of Angular is preferred.
• Knowledge of Stored Procedures and experience with a relational database (MSSQL 2012 or higher).
• Solid understanding of object-oriented development principles
• Working knowledge of web, HTML, CSS, JavaScript, and the Bootstrap framework
• Strong understanding of object-oriented programming
• Ability to create reusable C# libraries
• Must be able to write clean comments, readable C# code, and the ability to self-learn.
• Working knowledge of GIT

Qualities required :

Over above tech skill we prefer to have

• Good communication and Time Management Skill.
• Good team player and ability to contribute on a individual basis.
• 
  
• We provide the best learning and growth environment for candidates.

Skills:

    NET Core

   .NET Framework

    ASP.NET Core

    ASP.NET MVC

    ASP.NET Web API  

   C#

   HTML

Title:- Data Scientist

Experience:-6 years

Work Mode:- Onsite

Primary Skills:- Data Science, SQL, Python, Data Modelling, Azure, AWS, Banking Domain (BFSI/NBFC)

Qualification:- Any

Roles & Responsibilities:-

1.  Acquiring, cleaning, and preprocessing raw data for analysis.

2.  Utilizing statistical methods and tools for analyzing and interpreting complex  datasets.

3.  Developing and implementing machine learning models for predictive analysis.

4.  Creating visualizations to effectively communicate insights to both technical and   non-technical stakeholders.

5.  Collaborating with cross-functional teams, including data engineers, business   analysts, and domain experts.

6.  Evaluating and optimizing the performance of machine learning models for   accuracy and efficiency.

7.  Identifying patterns and trends within data to inform business decision-making.

8.  Staying updated on the latest advancements in data science, machine learning, and  relevant technologies.

Requirement:- 

1.  Experience with modeling techniques such as Linear Regression, clustering, and classification techniques.

2.  Must have a passion for data, structured or unstructured.  0.6 – 5 years of hands-on experience with Python and SQL is a must.

3.   Should have sound experience in data mining, data analysis and machine learning techniques.

4.  Excellent critical thinking, verbal and written communications skills.

5.  Ability and desire to work in a proactive, highly engaging, high-pressure, client service environment.

6.   Good presentation skills.

This person MUST have:

• B.E Computer Science or equivalent.

• In-depth knowledge of machine learning algorithms and their applications including practical experience with and theoretical understanding of algorithms for classification, regression and clustering.
• Hands-on experience in computer vision and deep learning projects to solve real world problems involving vision tasks such as object detection, Object tracking, instance segmentation, activity detection, depth estimation, optical flow, multi-view geometry, domain adaptation etc.
• Strong understanding of modern and traditional Computer Vision Algorithms.
• Experience in one of the Deep Learning Frameworks / Networks: PyTorch, TensorFlow, Darknet(YOLO v4 v5), U-Net, Mask R-CNN, EfficientDet,BERT etc.
• Proficiency with CNN architectures such as ResNet, VGG, UNet, MobileNet, pix2pix, and CycleGAN.
• Experienced user of libraries such as OpenCV, scikit-learn, matplotlib and pandas.
• Ability to transform research articles into working solutions to solve real-world problems.
• High proficiency in Python programming knowledge.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Strong communication skills.

Experience:

• Min 2 year experience
• Startup experience is a must. 

Location:

• Remote developer

Timings:

• 40 hours a week but with 4 hours a day overlapping with the client timezone.  Typically clients are in the California PST Timezone.

Position:

• Full time/Direct
• We have great benefits such as PF, medical insurance, 12 annual company holidays, 12 PTO leaves per year, annual increments, Diwali bonus, spot bonuses and other incentives etc.
• We dont believe in locking in people with large notice periods.  You will stay here because you love the company.  We have only a 15 days notice period.

• Perform research and development on Machine Learning specifically in the areas of Speech Recognition, Digital signal processing, audio signal processing, NaturalLanguage processing, Natural Language Understanding
• Read and keep up with the research in Speech recognition, Machine Learning, Deep

• Understand and implement research papers to the business problem and build the

• Contribute to applied research and open source community
• Mentor and guide team members

Skills- Informatica with Big Data Management

1.Minimum 6 to 8 years of experience in informatica BDM development
2.Experience working on Spark/SQL
3.Develops informtica mapping/Sql 

We are actively seeking a Senior Data Engineer experienced in building data pipelines and integrations from 3rd party data sources by writing custom automated ETL jobs using Python. The role will work in partnership with other members of the Business Analytics team to support the development and implementation of new and existing data warehouse solutions for our clients. This includes designing database import/export processes used to generate client data warehouse deliverables.

Required skill

• Around 6- 8.5 years of experience and around 4+ years in AI / Machine learning space
• Extensive experience in designing large scale machine learning solution for the ML use case,  large scale deployments and establishing continues automated improvement / retraining framework.
• Strong experience in Python and Java is required.
• Hands on experience on Scikit-learn, Pandas, NLTK
• Experience in Handling of Timeseries data and associated techniques like Prophet, LSTM
• Experience in Regression, Clustering, classification algorithms
• Extensive experience in buildings traditional Machine Learning SVM, XGBoost, Decision tree and Deep Neural Network models like RNN, Feedforward is required.
• Experience in AutoML like TPOT or other
• Must have strong hands on experience in Deep learning frameworks like Keras, TensorFlow or PyTorch 
• Knowledge of Capsule Network or reinforcement learning, SageMaker is a desirable skill
• Understanding of Financial domain is desirable skill

 Responsibilities 

• Design and implementation of solutions for ML Use cases
• Productionize System and Maintain those
• Lead and implement data acquisition process for ML work
• Learn new methods and model quickly and utilize those in solving use cases

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