Data Scientist - Kofax Accredited Developers
at a global provider of Business Process Management company
Job Description:
Role Summary:
The Robotics Process Automation Business Analyst helps define the business case for the proposed automation of the business processes by reviewing the current process, identifying the automation potential of the process, and the potential FTE takeout. The process architect working with the customer subject matter experts, and the technical architect designs the steps in the process that can be automated (with or without reengineering), and which serves as a basis for the development team to implement the robotics.
The business analyst will also review the design at the design stage, validates the developed automation to ensure it meets the intended design and the business benefits.
B1 – Data Scientist - Kofax Accredited Developers
Total Experience – 7-10 Years
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 , like Analytics, RPA, Technology and Project management teams
- Good understanding of compliance, data governance and risk control processes
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 with 15+ years of full time education
Similar jobs
Job Description
- Build state of the art langugae models to understand vernacular languages.
- Build and push machine learning models to optimise the results.
- Consume real-time data and build layers around that to leverage customer understanding.
- Our state-of-the-art models are ingesting and generating relevant search results for our customers weekly. Work directly with our current models to tune them to the abundant inflow of data as well as architecting new ones to further infuse AI into search workflows.
- Bee an integral part of Zevi, working on the core tech that makes our product what it is today. It doesn’t stop there though: As we collect more and more insights, get ready to shape the future of search.
Skills and Experience expected:
- Have at least 2 years of experience working with language models, building, fine-tuning, training them.
- Have closely read NLP publications and implemented some of them.
- Have designed and implemented a scalable ML infrastructure that is both secure and modular.
- Have pushed deep learning models in production.
- Have been responsible for breaking down and solving complex problems.
- Have developed engineering principles and designed processes/workflows.
- Have experience working in Python, sklearn, Pytorch, Tensorflow, and are an expert in at least one of those technologies.
What can you expect from Zevi ?
- Closely work with leading enterprise engineering teams.
- Be a part of highly motivated core team.
- Get access and contribute to all strategies being built by Zevi.
- Full ownership of your product line.
Job Location: India
Job Summary
We at CondeNast are looking for a data science manager for the content intelligence
workstream primarily, although there might be some overlap with other workstreams. The
position is based out of Chennai and shall report to the head of the data science team, Chennai
Responsibilities:
1. Ideate new opportunities within the content intelligence workstream where data Science can
be applied to increase user engagement
2. Partner with business and translate business and analytics strategies into multiple short-term
and long-term projects
3. Lead data science teams to build quick prototypes to check feasibility and value to business
and present to business
4. Formulate the business problem into an machine learning/AI problem
5. Review & validate models & help improve the accuracy of model
6. Socialize & present the model insights in a manner that business can understand
7. Lead & own the entire value chain of a project/initiative life cycle - Interface with business,
understand the requirements/specifications, gather data, prepare it, train,validate, test the
model, create business presentations to communicate insights, monitor/track the performance
of the solution and suggest improvements
8. Work closely with ML engineering teams to deploy models to production
9. Work closely with data engineering/services/BI teams to help develop data stores, intuitive
visualizations for the products
10. Setup career paths & learning goals for reportees & mentor them
Required Skills:
1. 5+ years of experience in leading Data Science & Advanced analytics projects with a focus on
building recommender systems and 10-12 years of overall experience
2. Experience in leading data science teams to implement recommender systems using content
based, collaborative filtering, embedding techniques
3. Experience in building propensity models, churn prediction, NLP - language models,
embeddings, recommendation engine etc
4. Master’s degree with an emphasis in a quantitative discipline such as statistics, engineering,
economics or mathematics/ Degree programs in data science/ machine learning/ artificial
intelligence
5. Exceptional Communication Skills - verbal and written
6. Moderate level proficiency in SQL, Python
7. Needs to have demonstrated continuous learning through external certifications, degree
programs in machine learning & artificial intelligence
8. Knowledge of Machine learning algorithms & understanding of how they work
9. Knowledge of Reinforcement Learning
Preferred Qualifications
1. Expertise in libraries for data science - pyspark(Databricks), scikit-learn, pandas, numpy,
matplotlib, pytorch/tensorflow/keras etc
2. Working Knowledge of deep learning models
3. Experience in ETL/ data engineering
4. Prior experience in e-commerce, media & publishing domain is a plus
5. Experience in digital advertising is a plus
About Condé Nast
CONDÉ NAST INDIA (DATA)
Over the years, Condé Nast successfully expanded and diversified into digital, TV, and social
platforms - in other words, a staggering amount of user data. Condé Nast made the right move
to invest heavily in understanding this data and formed a whole new Data team entirely
dedicated to data processing, engineering, analytics, and visualization. This team helps drive
engagement, fuel process innovation, further content enrichment, and increase market
revenue. The Data team aimed to create a company culture where data was the common
language and facilitate an environment where insights shared in real-time could improve
performance.
The Global Data team operates out of Los Angeles, New York, Chennai, and London. The team
at Condé Nast Chennai works extensively with data to amplify its brands' digital capabilities and
boost online revenue. We are broadly divided into four groups, Data Intelligence, Data
Engineering, Data Science, and Operations (including Product and Marketing Ops, Client
Services) along with Data Strategy and monetization. The teams built capabilities and products
to create data-driven solutions for better audience engagement.
What we look forward to:
We want to welcome bright, new minds into our midst and work together to create diverse
forms of self-expression. At Condé Nast, we encourage the imaginative and celebrate the
extraordinary. We are a media company for the future, with a remarkable past. We are Condé
Nast, and It Starts Here.
Roles and Responsibilities
- Managing available resources such as hardware, data, and personnel so that deadlines are met.
- Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
- Exploring 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
- Defining validation framework and establish a process to ensure acceptable data quality criteria are met
- Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
- Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
- Device self-learning strategies through analysis of errors from the models
- Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
- Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
- Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.
Preferred Technical & Professional expertise
- Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
- At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
- In-depth knowledge of cloud analytics tools.
- Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
- Ability to evaluate hardware selection for running ML models for optimal performance
- Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
- Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
- Deep analytical thinking with excellent problem-solving abilities
- Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
- Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
- Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
- Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards
In this role, we are looking for:
- A problem-solving mindset with the ability to understand business challenges and how to apply your analytics expertise to solve them.
- The unique person who can present complex mathematical solutions in a simple manner that most will understand, using data visualization techniques to tell a story with data.
- An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice.
- A team mentality, empowered by the ability to work with a diverse set of individuals.
- A passion for data, with a particular emphasis on data visualization.
Basic Qualifications
- A Bachelor’s degree in Data Science, Math, Statistics, Computer Science or related field with an emphasis on data analytics.
- 5+ Years professional experience, preferably in a data analyst / data scientist role or similar, with proven results in a data analyst role.
- 3+ Years professional experience in a leadership role guiding high-performing, data-focused teams with a track record of building and developing talent.
- Proficiency in your statistics / analytics / visualization tool of choice, but preferably in the Microsoft Azure Suite, including PowerBI and/or AzureML.
Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
Hammoq Inc is a rapidly growing startup in the reselling sector. Our app provides product listings, cross-platform data analytics, and Cross-platform delisting as our core services.
Launched Web app in 2020 and iOS app at the start of 2021, we are continuing our exponential growth, and we were hoping you could play a core role in our mission.
Hammoq is looking for a Senior ML/Machine Vision Architect / Researcher, an expert in Deep Learning, to join our passionate developers' team to create our unique SaaS web app.
The ideal candidate will be responsible for developing new Machine Learning / Machine vision models according to the business needs.
*What you'll do
- You’ll lead the ML R&D process at Hammoq.
- You will build ML architectures to optimise the process.
- You'll collaborate with our hardworking, nimble, and supportive team through daily standups, company presentations, product demos, slack discussions
- You'll work on solving machine vision / Machine Learning problems and implementations.
- You'll use ML libraries of IOS and Android to build and run models on the mobile devices
Skills and expertise that will help you succeed
- Must have experience working with OpenCV, TensorFlow, and Keras environment
- Must have the ability to develop your own models.
- Working experience of training and deploying computer vision models
- Experience in Computer Vision and Machine Learning (including Deep Learning) algorithms.
- Experience in image analytics - including feature extraction, object detection, classification, and tracking
- Experience in image manipulation
- PhD in Computer Vision , Machine Learning, Machine Vision or any related field is a must.
- Strong programming skills in Python, including NumPy, Scikit Learn, Pandas, and Matplotlib
- Self-governing analytical problem-solving skills for efficient and uninterrupted development of solutions
- Strong communications skills for an adequate description of technical concepts to others
Nice to have
- Experience in building APIs implementing ML models
- Knowledge or basic understanding of any Cloud ML technologies or Cloud ML service providers.
- Experience in the e-commerce industry
o Strong Python development skills, with 7+ yrs. experience with SQL.
o A bachelor or master’s degree in Computer Science or related areas
o 5+ years of experience in data integration and pipeline development
o Experience in Implementing Databricks Delta lake and data lake
o Expertise designing and implementing data pipelines using modern data engineering approach and tools: SQL, Python, Delta Lake, Databricks, Snowflake Spark
o Experience in working with multiple file formats (Parque, Avro, Delta Lake) & API
o experience with AWS Cloud on data integration with S3.
o Hands on Development experience with Python and/or Scala.
o Experience with SQL and NoSQL databases.
o Experience in using data modeling techniques and tools (focused on Dimensional design)
o Experience with micro-service architecture using Docker and Kubernetes
o Have experience working with one or more of the public cloud providers i.e. AWS, Azure or GCP
o Experience in effectively presenting and summarizing complex data to diverse audiences through visualizations and other means
o Excellent verbal and written communications skills and strong leadership capabilities
Skills:
ML
MOdelling
Python
SQL
Azure Data Lake, dataFactory, Databricks, Delta Lake
Work shift: Day time
- Strong problem-solving skills with an emphasis on product development.
insights from large data sets.
• Experience in building ML pipelines with Apache Spark, Python
• Proficiency in implementing end to end Data Science Life cycle
• Experience in Model fine-tuning and advanced grid search techniques
• Experience working with and creating data architectures.
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural
networks, etc.) and their real-world advantages/drawbacks.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,
statistical tests and proper usage, etc.) and experience with applications.
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
• Develop company A/B testing framework and test model quality.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.
Key skills:
● Strong knowledge in Data Science pipelines with Python
● Object-oriented programming
● A/B testing framework and model fine-tuning
● Proficiency in using sci-kit, NumPy, and pandas package in python
Nice to have:
● Ability to work with containerized solutions: Docker/Compose/Swarm/Kubernetes
● Unit testing, Test-driven development practice
● DevOps, Continuous integration/ continuous deployment experience
● Agile development environment experience, familiarity with SCRUM
● Deep learning knowledge
We are looking for an engineer with ML/DL background.
Ideal candidate should have the following skillset
1) Python
2) Tensorflow
3) Experience building and deploying systems
4) Experience with Theano/Torch/Caffe/Keras all useful
5) Experience Data warehousing/storage/management would be a plus
6) Experience writing production software would be a plus
7) Ideal candidate should have developed their own DL architechtures apart from using open source architechtures.
8) Ideal candidate would have extensive experience with computer vision applications
Candidates would be responsible for building Deep Learning models to solve specific problems. Workflow would look as follows:
1) Define Problem Statement (input -> output)
2) Preprocess Data
3) Build DL model
4) Test on different datasets using Transfer Learning
5) Parameter Tuning
6) Deployment to production
Candidate should have experience working on Deep Learning with an engineering degree from a top tier institute (preferably IIT/BITS or equivalent)