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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.

 

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 

 

Responsibilities:
• 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

Role : Senior Customer Scientist 

Experience : 6-8 Years 

Location : Chennai (Hybrid) 
 
 

Who are we? 
 
 

A young, fast-growing AI and big data company, with an ambitious vision to simplify the world’s choices. Our clients are top-tier enterprises in the banking, e-commerce and travel spaces. They use our core AI-based choice engine http://maya.ai/">maya.ai, to deliver personal digital experiences centered around taste. The http://maya.ai/">maya.ai platform now touches over 125M customers globally. You’ll find Crayon Boxes in Chennai and Singapore. But you’ll find Crayons in every corner of the world. Especially where our client projects are – UAE, India, SE Asia and pretty soon the US. 
 
 

Life in the Crayon Box is a little chaotic, largely dynamic and keeps us on our toes! Crayons are a diverse and passionate bunch. Challenges excite us. Our mission drives us. And good food, caffeine (for the most part) and youthful energy fuel us. Over the last year alone, Crayon has seen a growth rate of 3x, and we believe this is just the start. 
 

 
We’re looking for young and young-at-heart professionals with a relentless drive to help Crayon double its growth. Leaders, doers, innovators, dreamers, implementers and eccentric visionaries, we have a place for you all. 
 

 
 

Can you say “Yes, I have!” to the below? 
 
 

1. Experience with exploratory analysis, statistical analysis, and model development 
    

1. Knowledge of advanced analytics techniques, including Predictive Modelling (Logistic regression), segmentation, forecasting, data mining, and optimizations 
    

1. Knowledge of software packages such as SAS, R, Rapidminer for analytical modelling and data management. 
    

1. Strong experience in SQL/ Python/R working efficiently at scale with large data sets 
    

1. Experience in using Business Intelligence tools such as PowerBI, Tableau, Metabase for business applications 
    

 
 

 

Can you say “Yes, I will!” to the below? 
 
 

1. Drive clarity and solve ambiguous, challenging business problems using data-driven approaches. Propose and own data analysis (including modelling, coding, analytics) to drive business insight and facilitate decisions. 
    

1. Develop creative solutions and build prototypes to business problems using algorithms based on machine learning, statistics, and optimisation, and work with engineering to deploy those algorithms and create impact in production. 
    

1. Perform time-series analyses, hypothesis testing, and causal analyses to statistically assess the relative impact and extract trends 
    

1. Coordinate individual teams to fulfil client requirements and manage deliverable 
    

1. Communicate and present complex concepts to business audiences 
    

1. Travel to client locations when necessary  

 

 

Crayon is an equal opportunity employer. Employment is based on a person's merit and qualifications and professional competences. Crayon does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, marital status, pregnancy or related.  
 
 

More about Crayon: https://www.crayondata.com/">https://www.crayondata.com/  
 

More about http://maya.ai/">maya.ai: https://maya.ai/">https://maya.ai/  

 

 

THE IDEAL CANDIDATE WILL

 

• Engage with executive level stakeholders from client's team to translate business problems to high level solution approach
• Partner closely with practice, and technical teams to craft well-structured comprehensive proposals/ RFP responses clearly highlighting Tredence’s competitive strengths relevant to Client's selection criteria
• Actively explore the client’s business and formulate solution ideas that can improve process efficiency and cut cost, or achieve growth/revenue/profitability targets faster
• Work hands-on across various MLOps problems and provide thought leadership
• Grow and manage large teams with diverse skillsets
• Collaborate, coach, and learn with a growing team of experienced Machine Learning Engineers and Data Scientists

 

 

 

ELIGIBILITY CRITERIA

 

• BE/BTech/MTech (Specialization/courses in ML/DS)
• At-least 7+ years of Consulting services delivery experience
• Very strong problem-solving skills & work ethics
• Possesses strong analytical/logical thinking, storyboarding and executive communication skills
• 5+ years of experience in Python/R, SQL
• 5+ years of experience in NLP algorithms, Regression & Classification Modelling, Time Series Forecasting
• Hands on work experience in DevOps
• Should have good knowledge in different deployment type like PaaS, SaaS, IaaS
• Exposure on cloud technologies like Azure, AWS or GCP
• Knowledge in python and packages for data analysis (scikit-learn, scipy, numpy, pandas, matplotlib).
• Knowledge of Deep Learning frameworks: Keras, Tensorflow, PyTorch, etc
• Experience with one or more Container-ecosystem (Docker, Kubernetes)
• Experience in building orchestration pipeline to convert plain python models into a deployable API/RESTful endpoint.
• Good understanding of OOP & Data Structures concepts

 

 

Nice to Have:

 

• Exposure to deployment strategies like: Blue/Green, Canary, AB Testing, Multi-arm Bandit
• Experience in Helm is a plus
• Strong understanding of data infrastructure, data warehouse, or data engineering

 

You can expect to –

• Work with world’ biggest retailers and help them solve some of their most critical problems. Tredence is a preferred analytics vendor for some of the largest Retailers across the globe
• Create multi-million Dollar business opportunities by leveraging impact mindset, cutting edge solutions and industry best practices.
• Work in a diverse environment that keeps evolving
• Hone your entrepreneurial skills as you contribute to growth of the organization

 

 

• 5+ years of experience in a Data Engineering role on cloud environment

• Must have good experience in Scala/PySpark (preferably on data-bricks environment)

• Extensive experience with Transact-SQL.
• Experience in Data-bricks/Spark.

• Strong experience in Dataware house projects
• Expertise in database development projects with ETL processes.
• Manage and maintain data engineering pipelines

• Develop batch processing, streaming and integration solutions
• Experienced in building and operationalizing large-scale enterprise data solutions and applications

• Using one or more of Azure data and analytics services in combination with custom solutions
• Azure Data Lake, Azure SQL DW (Synapse), and SQL Database products or equivalent products from other cloud services providers

• In-depth understanding of data management (e. g. permissions, security, and monitoring).
• Cloud repositories for e.g. Azure GitHub, Git
• Experience in an agile environment (Prefer Azure DevOps).

Good to have

• Manage source data access security
• Automate Azure Data Factory pipelines
• Continuous Integration/Continuous deployment (CICD) pipelines, Source Repositories
• Experience in implementing and maintaining CICD pipelines
• Power BI understanding, Delta Lake house architecture
• Knowledge of software development best practices.
• Excellent analytical and organization skills.
• Effective working in a team as well as working independently.
• Strong written and verbal communication skills.
• Expertise in database development projects and ETL processes.

Position: Big Data Engineer

What You'll Do

Punchh is seeking to hire Big Data Engineer at either a senior or tech lead level. Reporting to the Director of Big Data, he/she will play a critical role in leading Punchh’s big data innovations. By leveraging prior industrial experience in big data, he/she will help create cutting-edge data and analytics products for Punchh’s business partners.

This role requires close collaborations with data, engineering, and product organizations. His/her job functions include

• Work with large data sets and implement sophisticated data pipelines with both structured and structured data.
• Collaborate with stakeholders to design scalable solutions.
• Manage and optimize our internal data pipeline that supports marketing, customer success and data science to name a few.
• A technical leader of Punchh’s big data platform that supports AI and BI products.
• Work with infra and operations team to monitor and optimize existing infrastructure 
• Occasional business travels are required.

What You'll Need

• 5+ years of experience as a Big Data engineering professional, developing scalable big data solutions.
• Advanced degree in computer science, engineering or other related fields.
• Demonstrated strength in data modeling, data warehousing and SQL.
• Extensive knowledge with cloud technologies, e.g. AWS and Azure.
• Excellent software engineering background. High familiarity with software development life cycle. Familiarity with GitHub/Airflow.
• Advanced knowledge of big data technologies, such as programming language (Python, Java), relational (Postgres, mysql), NoSQL (Mongodb), Hadoop (EMR) and streaming (Kafka, Spark).
• Strong problem solving skills with demonstrated rigor in building and maintaining a complex data pipeline.
• Exceptional communication skills and ability to articulate a complex concept with thoughtful, actionable recommendations.

• 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.
• Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
• 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.

• Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
• Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
• 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 5+ 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: Hadoop, Spark, Kafka, etc.
• Experience with relational SQL and NoSQL databases, including Postgres and Cassandra.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• 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, C++, Scala, etc.

Job Overview :We are looking for an experienced Data Science professional to join our Product team and lead the data analytics team and manage the processes and people responsible for accurate data collection, processing, modelling and analysis. The ideal candidate has a knack for seeing solutions in sprawling data sets and the business mindset to convert insights into strategic opportunities for our clients. The incumbent will work closely with leaders across product, sales, and marketing to support and implement high-quality, data-driven decisions. They will ensure data accuracy and consistent reporting by designing and creating optimal processes and procedures for analytics employees to follow. They will use advanced data modelling, predictive modelling, natural language processing and analytical techniques to interpret key findings.Responsibilities for Analytics Manager :- Build, develop and maintain data models, reporting systems, data automation systems, dashboards and performance metrics support that support key business decisions.- Design and build technical processes to address business issues.- Manage and optimize processes for data intake, validation, mining and engineering as well as modelling, visualization and communication deliverables.- Examine, interpret and report results to stakeholders in leadership, technology, sales, marketing and product teams.- Develop and implement quality controls and standards to ensure quality standards- Anticipate future demands of initiatives related to people, technology, budget and business within your department and design/implement solutions to meet these needs.- Communicate results and business impacts of insight initiatives to stakeholders within and outside of the company.- Lead cross-functional projects using advanced data modelling and analysis techniques to discover insights that will guide strategic decisions and uncover optimization opportunities.Qualifications for Analytics Manager :- Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple cloud-based data sources- Strong SQL skills, ability to perform effective querying- Understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analysing data, drawing conclusions, and developing actionable recommendations for business units.- Experience and knowledge of statistical modelling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.- Experience working with and creating databases and dashboards using all relevant data to inform decisions.- Strong problem solving, quantitative and analytical abilities.- Strong ability to plan and manage numerous processes, people and projects simultaneously.- Excellent communication, collaboration and delegation skills.- We- re looking for someone with at least 5 years of experience in a position monitoring, managing and drawing insights from data, and someone with at least 3 years of experience leading a team. The right candidate will also be proficient and experienced with the following tools/programs :- Strong programming skills with querying languages: R, Python etc.- Experience with big data tools like Hadoop- Experience with data visualization tools: Tableau, d3.js, etc.- Experience with Excel, Word, and PowerPoint.