Machine Learning Engineer
As a machine learning engineer on the team, you will
• Help science and product teams innovate in developing and improving end-to-end
solutions to machine learning-based security/privacy control
• Partner with scientists to brainstorm and create new ways to collect/curate data
• Design and build infrastructure critical to solving problems in privacy-preserving machine
learning
• Help team self-organize and follow machine learning best practice.
Basic Qualifications
• 4+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• 4+ years of programming experience with at least one modern language such as Java,
C++, or C# including object-oriented design
• 4+ years of professional software development experience
• 4+ years of experience as a mentor, tech lead OR leading an engineering team
• 4+ years of professional software development experience in Big Data and Machine
Learning Fields
• Knowledge of common ML frameworks such as Tensorflow, PyTorch
• Experience with cloud provider Machine Learning tools such as AWS SageMaker
• Programming experience with at least two modern language such as Python, Java, C++,
or C# including object-oriented design
• 3+ years of experience contributing to the architecture and design (architecture, design
patterns, reliability and scaling) of new and current systems
• Experience in python
• BS in Computer Science or equivalent
About Contact Center software that leverages AI to improve custome
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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.
o You’re both relentless and kind, and don’t see these as being mutually
exclusive
o You have a self-directed learning style, an insatiable curiosity, and a
hands-on execution mindset
o You have deep experience working with product and engineering teams
to launch machine learning products that users love in new or rapidly
evolving markets
o You flourish in uncertain environments and can turn incomplete,
conflicting, or ambiguous inputs into solid data-science action plans
o You bring best practices to feature engineering, model development, and
ML operations
o Your experience in deploying and monitoring the performance of models
in production enables us to implement a best-in-class solution
o You have exceptional writing and speaking skills with a talent for
articulating how data science can be applied to solve customer problems
Must-Have Qualifications
o Graduate degree in engineering, data science, mathematics, physics, or
another quantitative field
o 5+ years of hands-on experience in building and deploying production-
grade ML models with ML frameworks (TensorFlow, Keras, PyTorch) and
libraries like scikit-learn
o Track-record in building ML pipelines for time series, classification, and
predictive applications
o Expert level skills in Python for data analysis and visualization, hypothesis
testing, and model building
o Deep experience with ensemble ML approaches including random forests
and xgboost, and experience with databases and querying models for
structured and unstructured data
o A knack for using data visualization and analysis tools to tell a story
o You naturally think quantitatively about problems and work backward
from a customer outcome
What’ll make you stand out (but not required)
o You have a keen awareness or interest in network analysis/graph analysis
or NLP
o You have experience in distributed systems and graph databases
o You have a strong connection to finance teams or closely related
domains, the challenges they face, and a deep appreciation for their
aspirations
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.
- 2+ Years experience as an ETL developer with strong data architecture knowledge around data warehousing concepts, SQL development and optimization, and operational support models.
- Experience using Python to automate ETL/Data Processes jobs.
- Design and develop ETL and data processing solutions using data integration tools, python scripts, and AWS / Azure / On-Premise Environment.
- Experience / Willingness to learn AWS Glue / AWS Data Pipeline / Azure Data Factory for Data Integration.
- Develop and create transformation queries, views, and stored procedures for ETL processes, and process automation.
- Document data mappings, data dictionaries, processes, programs, and solutions as per established standards for data governance.
- Work with the data analytics team to assess and troubleshoot potential data quality issues at key intake points such as validating control totals at intake and then upon transformation, and transparently build lessons learned into future data quality assessments
- Solid experience with data modeling, business logic, and RESTful APIs.
- Solid experience in the Linux environment.
- Experience with NoSQL / PostgreSQL preferred
- Experience working with databases such as MySQL, NoSQL, and Postgres, and enterprise-level connectivity experience (such as connecting over TLS and through proxies).
- Experience with NGINX and SSL.
- Performance tune data processes and SQL queries, and recommend and implement data process optimization and query tuning techniques.
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
Your mission is to help lead team towards creating solutions that improve the way our business is run. Your knowledge of design, development, coding, testing and application programming will help your team raise their game, meeting your standards, as well as satisfying both business and functional requirements. Your expertise in various technology domains will be counted on to set strategic direction and solve complex and mission critical problems, internally and externally. Your quest to embracing leading-edge technologies and methodologies inspires your team to follow suit.
Responsibilities and Duties :
- As a Data Engineer you will be responsible for the development of data pipelines for numerous applications handling all kinds of data like structured, semi-structured &
unstructured. Having big data knowledge specially in Spark & Hive is highly preferred.
- Work in team and provide proactive technical oversight, advice development teams fostering re-use, design for scale, stability, and operational efficiency of data/analytical solutions
Education level :
- Bachelor's degree in Computer Science or equivalent
Experience :
- Minimum 5+ years relevant experience working on production grade projects experience in hands on, end to end software development
- Expertise in application, data and infrastructure architecture disciplines
- Expert designing data integrations using ETL and other data integration patterns
- Advanced knowledge of architecture, design and business processes
Proficiency in :
- Modern programming languages like Java, Python, Scala
- Big Data technologies Hadoop, Spark, HIVE, Kafka
- Writing decently optimized SQL queries
- Orchestration and deployment tools like Airflow & Jenkins for CI/CD (Optional)
- Responsible for design and development of integration solutions with Hadoop/HDFS, Real-Time Systems, Data Warehouses, and Analytics solutions
- Knowledge of system development lifecycle methodologies, such as waterfall and AGILE.
- An understanding of data architecture and modeling practices and concepts including entity-relationship diagrams, normalization, abstraction, denormalization, dimensional
modeling, and Meta data modeling practices.
- Experience generating physical data models and the associated DDL from logical data models.
- Experience developing data models for operational, transactional, and operational reporting, including the development of or interfacing with data analysis, data mapping,
and data rationalization artifacts.
- Experience enforcing data modeling standards and procedures.
- Knowledge of web technologies, application programming languages, OLTP/OLAP technologies, data strategy disciplines, relational databases, data warehouse development and Big Data solutions.
- Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals
Skills :
Must Know :
- Core big-data concepts
- Spark - PySpark/Scala
- Data integration tool like Pentaho, Nifi, SSIS, etc (at least 1)
- Handling of various file formats
- Cloud platform - AWS/Azure/GCP
- Orchestration tool - Airflow
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