Data Scientist

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 

 

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

 

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

 

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

 

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

 

#LI-Remote

Job Description: Be responsible for scaling our analytics capability across all internal disciplines and guide our strategic direction in regards to analytics Organize and analyze large, diverse data sets across multiple platforms Identify key insights and leverage them to inform and influence product strategy Technical Interactions with vendor or partners in technical capacity for scope/ approach & deliverables. Develops proof of concept to prove or disprove validity of concept. Working with all parts of the business to identify analytical requirements and formalize an approach for reliable, relevant, accurate, efficientreporting on those requirements Designing and implementing advanced statistical testing for customized problem solving Deliver concise verbal and written explanations of analyses to senior management that elevate findings into strategic recommendations Desired Candidate Profile: MTech / BE / BTech / MSc in CS or Stats or Maths, Operation Research, Statistics, Econometrics or in any quantitative field Experience in using Python, R, SAS Experience in working with large data sets and big data systems (SQL, Hadoop, Hive, etc.) Keen aptitude for large-scale data analysis with a passion for identifying key insights from data Expert working knowledge in various machine learning algorithms such XGBoost, SVM Etc. We are looking candidates from the following: Experience in Unsecured Loans & SME Loans analytics (cards, installment loans) - risk based pricing analytics Experience in Differential pricing / selection analytics (retail, airlines / travel etc). Experience in Digital product companies or Digital eCommerce with Product mindset and experience Experience in Fraud / Risk from Banks, NBFC / Fintech / Credit Bureau Experience in Online media with knowledge of media, online ads & sales (agencies) - Knowledge of DMP, DFP, Adobe/Omniture tools, Cloud Experience in Consumer Durable Loans lending companies (Experience in Credit Cards, Personal Loan - optional) Experience in Tractor Loans lending companies (Experience in Farm) Experience in Recovery, Collections analytics Experience in Marketing Analytics with Digital Marketing, Market Mix modelling, Advertising Technology

About Us

upGrad is an online education platform building the careers of tomorrow by offering the most industry-relevant programs in an immersive learning experience. Our mission is to create a new digital-first learning experience to deliver tangible career impact to individuals at scale. upGrad currently offers programs in Data Science, Machine Learning, Product Management, Digital Marketing, and Entrepreneurship, etc. upGrad is looking for people passionate about management and education to help design learning programs for working professionals to stay sharp and stay relevant and help build the careers of tomorrow.

• upGrad was awarded the Best Tech for Education by IAMAI for 2018-19

• upGrad was also ranked as one of the LinkedIn Top Startups 2018: The 25 most sought-

  after startups in India

• upGrad was earlier selected as one of the top ten most innovative companies in India

  by FastCompany.

• We were also covered by the Financial Times along with other disruptors in Ed-Tech

• upGrad is the official education partner for Government of India - Startup India

  program

• Our program with IIIT B has been ranked #1 program in the country in the domain of Artificial Intelligence and Machine Learning

   

  Role Summary

  Are you excited by the challenge and the opportunity of applying data-science and data- analytics techniques to the fast developing education technology domain? Do you look forward to, the sense of ownership and achievement that comes with innovating and creating data products from scratch and pushing it live into Production systems? Do you want to work with a team of highly motivated members who are on a mission to empower individuals through education?
  If this is you, come join us and become a part of the upGrad technology team. At upGrad the technology team enables all the facets of the business - whether it’s bringing efficiency to ourmarketing and sales initiatives, to enhancing our student learning experience, to empowering our content, delivery and student success teams, to aiding our student’s for their desired careeroutcomes. We play the part of bringing together data & tech to solve these business problems and opportunities at hand.
  We are looking for an highly skilled, experienced and passionate data-scientist who can come on-board and help create the next generation of data-powered education tech product. The ideal candidate would be someone who has worked in a Data Science role before wherein he/she is comfortable working with unknowns, evaluating the data and the feasibility of applying scientific techniques to business problems and products, and have a track record of developing and deploying data-science models into live applications. Someone with a strong math, stats, data-science background, comfortable handling data (structured+unstructured) as well as strong engineering know-how to implement/support such data products in Production environment.
  Ours is a highly iterative and fast-paced environment, hence being flexible, communicating well and attention-to-detail are very important too. The ideal candidate should be passionate about the customer impact and comfortable working with multiple stakeholders across the company.

  
  Roles & Responsibilities

  • • 3+ years of experience in analytics, data science, machine learning or comparable role
    • Bachelor's degree in Computer Science, Data Science/Data Analytics, Math/Statistics or related discipline 
    • Experience in building and deploying Machine Learning models in Production systems
    • Strong analytical skills: ability to make sense out of a variety of data and its relation/applicability to the business problem or opportunity at hand
    • Strong programming skills: comfortable with Python - pandas, numpy, scipy, matplotlib; Databases - SQL and noSQL
    • Strong communication skills: ability to both formulate/understand the business problem at hand as well as ability to discuss with non data-science background stakeholders 
    • Comfortable dealing with ambiguity and competing objectives

     

    Skills Required

    • Experience in Text Analytics, Natural Language Processing

    • Advanced degree in Data Science/Data Analytics or Math/Statistics

    • Comfortable with data-visualization tools and techniques

    • Knowledge of AWS and Data Warehousing

    • Passion for building data-products for Production systems - a strong desire to impact

      the product through data-science technique

About antuit.ai

 

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

 

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

 

The Role:

 

Antuit.ai is interested in hiring a Principal Data Scientist, this person will facilitate standing up standardization and automation ecosystem for ML product delivery, he will also actively participate in managing implementation, design and tuning of product to meet business needs.

 

Responsibilities:

 

Responsibilities includes, but are not limited to the following:

 

• Manage and provides technical expertise to the delivery team. This includes recommendation of solution alternatives, identification of risks and managing business expectations.
• Design, build reliable and scalable automated processes for large scale machine learning.
• Use engineering expertise to help design solutions to novel problems in software development, data engineering, and machine learning. 
• Collaborate with Business, Technology and Product teams to stand-up MLOps process.
• Apply your experience in making intelligent, forward-thinking, technical decisions to delivery ML ecosystem, including implementing new standards, architecture design, and workflows tools.
• Deep dive into complex algorithmic and product issues in production
• Own metrics and reporting for delivery team. 
• Set a clear vision for the team members and working cohesively to attain it.
• Mentor and coach team members

Qualifications and Skills:

 

Requirements

• Engineering degree in any stream
• Has at least 7 years of prior experience in building ML driven products/solutions
• Excellent programming skills in any one of the language C++ or Python or Java.
• Hands on experience on open source libraries and frameworks- Tensorflow,Pytorch, MLFlow, KubeFlow, etc.
• Developed and productized large-scale models/algorithms in prior experience
• Can drive fast prototypes/proof of concept in evaluating various technology, frameworks/performance benchmarks.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Good verbal, written and presentation skills.
• Ability to learn new skills and technologies.
• 3+ years working with retail or CPG preferred.
• Experience in forecasting and optimization problems, particularly in the CPG / Retail industry preferred.

 

Information Security Responsibilities

 

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC

 

Antuit.ai is an at-will, equal opportunity employer.  We consider applicants for all positions without regard to race, color, religion, national origin or ancestry, gender identity, sex, age (40+), marital status, disability, veteran status, or any other legally protected status under local, state, or federal law.

Responsibility

• Partnering with internal business owners (product, marketing, edit, etc.) to understand needs and develop custom analysis to optimize for user engagement and retention
• Good understanding of the underlying business and workings of cross functional teams for successful execution
• Design and develop analyses based on business requirement needs and challenges.
• Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.
• Providing statistical analysis on custom research projects and consult on A/B testing and other statistical analysis as needed. Other reports and custom analysis as required.
• Identify and use appropriate investigative and analytical technologies to interpret and verify results.
• Apply and learn a wide variety of tools and languages to achieve results
• Use best practices to develop statistical and/ or machine learning techniques to build models that address business needs.

Requirements

• 2 - 4 years  of relevant experience in Data science.
• Preferred education: Bachelor's degree in a technical field or equivalent experience.
• Experience in advanced analytics, model building, statistical modeling, optimization, and machine learning algorithms.
• Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection. Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.
• Strong with programming languages like Python and data processing using SQL or equivalent and ability to experiment with newer open source tools.
• Experience in normalizing data to ensure it is homogeneous and consistently formatted to enable sorting, query and analysis.
• Experience designing, developing, implementing and maintaining a database and programs to manage data analysis efforts.
• Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE).
• Experience in risk and credit score domains preferred.

We are a nascent quant hedge fund; we need to stage financial data and make it easy to run and re-run various preprocessing and ML jobs on the data.
- We are looking for an experienced data engineer to join our team.
- The preprocessing involves ETL tasks, using pyspark, AWS Glue, staging data in parquet formats on S3, and Athena

To succeed in this data engineering position, you should care about well-documented, testable code and data integrity. We have devops who can help with AWS permissions.
We would like to build up a consistent data lake with staged, ready-to-use data, and to build up various scripts that will serve as blueprints for various additional data ingestion and transforms.

If you enjoy setting up something which many others will rely on, and have the relevant ETL expertise, we’d like to work with you.

Responsibilities
- Analyze and organize raw data
- Build data pipelines
- Prepare data for predictive modeling
- Explore ways to enhance data quality and reliability
- Potentially, collaborate with data scientists to support various experiments

Requirements
- Previous experience as a data engineer with the above technologies

• Model design, feature planning, system infrastructure, production setup and monitoring, and release management. 
• Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc.
• Experience in selecting features, building and optimizing classifiers using machine learning techniques.
• Prior experience with data visualization tools, such as D3.js, GGplot, etc..
• Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc..
• Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders.
• Basic understanding of the banking industry is value add

Develop, process, cleanse and enhance data collection procedures from multiple data sources.
• Conduct & deliver experiments and proof of concepts to validate business ideas and potential value.
• Test, troubleshoot and enhance the developed models in a distributed environments to improve it's accuracy.
• Work closely with product teams to implement algorithms with Python and/or R.
• Design and implement scalable predictive models, classifiers leveraging machine learning, data regression.
• Facilitate integration with enterprise applications using APIs to enrich implementations

We aim to transform recruiting industry.