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Machine Learning (ML)We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.
Skills:
- 5+ years deploying Machine Learning pipelines in large enterprise production systems.
- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.
Roles and Responsibilities:
Deploying ML models into production, and scaling them to serve millions of customers.
Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.
Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.
Provide software design and programming support to projects.
Qualifications & Experience:
Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.
Data ScienceMachine Learning (ML)B1 – Data Scientist - Kofax Accredited Developers
Requirement – 3
Mandatory –
- Accreditation of Kofax KTA / KTM
- Experience in Kofax Total Agility Development – 2-3 years minimum
- Ability to develop and translate functional requirements to design
- Experience in requirement gathering, analysis, development, testing, documentation, version control, SDLC, Implementation and process orchestration
- Experience in Kofax Customization, writing Custom Workflow Agents, Custom Modules, Release Scripts
- Application development using Kofax and KTM modules
- Good/Advance understanding of Machine Learning /NLP/ Statistics
- Exposure to or understanding of RPA/OCR/Cognitive Capture tools like Appian/UI Path/Automation Anywhere etc
- Excellent communication skills and collaborative attitude
- Work with multiple teams and stakeholders within like Analytics, RPA, Technology and Project management teams
- Good understanding of compliance, data governance and risk control processes
Total Experience – 7-10 Years in BPO/KPO/ ITES/BFSI/Retail/Travel/Utilities/Service Industry
Good to have
- Previous experience of working on Agile & Hybrid delivery environment
- Knowledge of VB.Net, C#( C-Sharp ), SQL Server , Web services
Qualification -
- Masters in Statistics/Mathematics/Economics/Econometrics Or BE/B-Tech, MCA or MBA
Machine Learning (ML)Data Science
Deep Learning
PythonSkills: Machine Learning,Deep Learning,Artificial Intelligence,python.
Location:Chennai
Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI
Requirements:
· To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies
· Design and develop AI//ML models to be deployed across SG factories
· Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
· Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
· Prior experience in developing AI and ML models is required
· Experience with data from the Manufacturing Industry would be a plus
Roles and Responsibilities:
· Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
· Multitasking, good communication necessary
· Entrepreneurial attitude.
Greetings!!!!
We are looking for a data engineer for one of our premium clients for their Chennai and Tirunelveli location
Required Education/Experience
● Bachelor’s degree in computer Science or related field
● 5-7 years’ experience in the following:
● Snowflake, Databricks management,
● Python and AWS Lambda
● Scala and/or Java
● Data integration service, SQL and Extract Transform Load (ELT)
● Azure or AWS for development and deployment
● Jira or similar tool during SDLC
● Experience managing codebase using Code repository in Git/GitHub or Bitbucket
● Experience working with a data warehouse.
● Familiarity with structured and semi-structured data formats including JSON, Avro, ORC, Parquet, or XML
● Exposure to working in an agile work environment
Machine Learning (ML)Deep Learning• Charting learning journeys with knowledge graphs.
• Predicting memory decay based upon an advanced cognitive model.
• Ensure content quality via study behavior anomaly detection.
• Recommend tags using NLP for complex knowledge.
• Auto-associate concept maps from loosely structured data.
• Predict knowledge mastery.
• Search query personalization.
Requirements:
• 6+ years experience in AI/ML with end-to-end implementation.
• Excellent communication and interpersonal skills.
• Expertise in SageMaker, TensorFlow, MXNet, or equivalent.
• Expertise with databases (e. g. NoSQL, Graph).
• Expertise with backend engineering (e. g. AWS Lambda, Node.js ).
• Passionate about solving problems in education
About the company:
VakilSearch is a technology-driven platform, offering services that cover the legal needs of startups and established businesses. Some of our services include incorporation, government registrations & filings, accounting, documentation and annual compliances. In addition, we offer a wide range of services to individuals, such as property agreements and tax filings. Our mission is to provide one-click access to individuals and businesses for all their legal and professional needs.
You can learn more about us at https://vakilsearch.com/">vakilsearch.com.
About the role:
A successful data analyst needs to have a combination of technical as well leadership skills. A background in Mathematics, Statistics, Computer Science, Information Management can serve as a solid foundation to build your career as a data analyst at VakilSearch.
Why to join Vakilsearch:
- Unlimited opportunities to grow
- Flat hierarchy
- Encouraging environment to unleash your out of box thinking skills
Responsibilities:
- Preparing reports for the stakeholders and the management, enabling them to take important decisions based on various facts and trends.
- Using automated tools to extract data from primary and secondary sources
- Identify and recommend the right product metrics to be analysed and tracked for every feature/problem statement.
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
Required skills:
- Bachelor’s degree from an accredited university or college in computer science or graduate from data science related program
- Minimum of 0 - 2 years experience in analysing
Requirements
PythonResponsibilities:
- Be the analytical expert in Kaleidofin, managing ambiguous problems by using data to execute sophisticated quantitative modeling and deliver actionable insights.
- Develop comprehensive skills including project management, business judgment, analytical problem solving and technical depth.
- Become an expert on data and trends, both internal and external to Kaleidofin.
- Communicate key state of the business metrics and develop dashboards to enable teams to understand business metrics independently.
- Collaborate with stakeholders across teams to drive data analysis for key business questions, communicate insights and drive the planning process with company executives.
- Automate scheduling and distribution of reports and support auditing and value realization.
- Partner with enterprise architects to define and ensure proposed.
- Business Intelligence solutions adhere to an enterprise reference architecture.
- Design robust data-centric solutions and architecture that incorporates technology and strong BI solutions to scale up and eliminate repetitive tasks.
- Experience leading development efforts through all phases of SDLC.
- 2+ years "hands-on" experience designing Analytics and Business Intelligence solutions.
- Experience with Quicksight, PowerBI, Tableau and Qlik is a plus.
- Hands on experience in SQL, data management, and scripting (preferably Python).
- Strong data visualisation design skills, data modeling and inference skills.
- Hands-on and experience in managing small teams.
- Financial services experience preferred, but not mandatory.
- Strong knowledge of architectural principles, tools, frameworks, and best practices.
- Excellent communication and presentation skills to communicate and collaborate with all levels of the organisation.
- Preferred candidates with less than 30 days notice period.
at Altimetrik
Bigdata with cloud:
Experience : 5-10 years
Location : Hyderabad/Chennai
Notice period : 15-20 days Max
1. Expertise in building AWS Data Engineering pipelines with AWS Glue -> Athena -> Quick sight
2. Experience in developing lambda functions with AWS Lambda
3. Expertise with Spark/PySpark – Candidate should be hands on with PySpark code and should be able to do transformations with Spark
4. Should be able to code in Python and Scala.
5. Snowflake experience will be a plus
Amazon Web Services (AWS)PythonLocation: Chennai- Guindy Industrial Estate
Duration: Full time role
Company: Mobile Programming (https://www.mobileprogramming.com/" target="_blank">https://www.
Client Name: Samsung
We are looking for a Data Engineer to join our growing team of analytics experts. The hire will be
responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing
data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline
builder and data wrangler who enjoy optimizing data systems and building them from the ground up.
The Data Engineer will support our software developers, database architects, data analysts and data
scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout
ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple
teams, systems and products.
Responsibilities for Data Engineer
Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes,
optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data
from a wide variety of data sources using SQL and AWS big data technologies.
Build analytics tools that utilize the data pipeline to provide actionable insights into customer
acquisition, operational efficiency and other key business performance metrics.
Work with stakeholders including the Executive, Product, Data and Design teams to assist with
data-related technical issues and support their data infrastructure needs.
Create data tools for analytics and data scientist team members that assist them in building and
optimizing our product into an innovative industry leader.
Work with data and analytics experts to strive for greater functionality in our data systems.
Qualifications for Data Engineer
Experience building and optimizing big data ETL pipelines, architectures and data sets.
Advanced working SQL knowledge and experience working with relational databases, query
authoring (SQL) as well as working familiarity with a variety of databases.
Experience performing root cause analysis on internal and external data and processes to
answer specific business questions and identify opportunities for improvement.
Strong analytic skills related to working with unstructured datasets.
Build processes supporting data transformation, data structures, metadata, dependency and
workload management.
A successful history of manipulating, processing and extracting value from large disconnected
datasets.
Working knowledge of message queuing, stream processing and highly scalable ‘big data’ data
stores.
Strong project management and organizational skills.
Experience supporting and working with cross-functional teams in a dynamic environment.
We are looking for a candidate with 3-6 years of experience in a Data Engineer role, who has
attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
Experience with big data tools: Spark, Kafka, HBase, Hive etc.
Experience with relational SQL and NoSQL databases
Experience with AWS cloud services: EC2, EMR, RDS, Redshift
Experience with stream-processing systems: Storm, Spark-Streaming, etc.
Experience with object-oriented/object function scripting languages: Python, Java, Scala, etc.
Skills: Big Data, AWS, Hive, Spark, Python, SQL
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