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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

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 

 

Role - Data Scientist / Machine Learning Scientist / Deep Learning Engineer -: 3 - 5 yrs experienced Programming Must Know:- Python, Tensorflow, Keras, Kafka, Spark Must have worked in Video Analytics with at least 2 Deep Learning Models like R-CNN, LSTM, Object Detection Models like YOLO, Object tracking Models like Deep SORT Must have good model training and testing experience with Structured(statistical machine learning) and Unstructured Data Must be good with Statistics. Good to have Data visualization experience in Python or any data visualization tool. Good to have Kubernetes, Multiprocessing experience, MLops like docker, hydra etc

Team:- We are a team of 9 data scientists working on Video Analytics Projects, Data Analytics projects for internal AI requirements of Reliance Industries as well for the external business. At a time, we make progress on multiple projects(atleast 4) in Video Analytics or Data Analytics.

Responsibilities

• Work on execution and scheduling of all tasks related to assigned projects' deliverable dates
• Optimize and debug existing codes to make them scalable and improve performance
• Design, development, and delivery of tested code and machine learning models into production environments
• Work effectively in teams, managing and leading teams
• Provide effective, constructive feedback to the delivery leader
• Manage client expectations and work with an agile mindset with machine learning and AI technology
• Design and prototype data-driven solutions

Eligibility

• Highly experienced in designing, building, and shipping scalable and production-quality machine learning algorithms in the field of Python applications
• Working knowledge and experience in NLP core components (NER, Entity Disambiguation, etc.)
• In-depth expertise in Data Munging and Storage (Experienced in SQL, NoSQL, MongoDB, Graph Databases)
• Expertise in writing scalable APIs for machine learning models
• Experience with maintaining code logs, task schedulers, and security
• Working knowledge of machine learning techniques, feed-forward, recurrent and convolutional neural networks, entropy models, supervised and unsupervised learning
• Experience with at least one of the following: Keras, Tensorflow, Caffe, or PyTorch

Role : 

• Understand and translate statistics and analytics to address business problems
• Responsible for helping in data preparation and data pull, which is the first step in machine learning
• Should be able to do cut and slice data to extract interesting insights from the data
• Model development for better customer engagement and retention
• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Working on strategy development to increase business revenue

 

Requirements:

• Hands on experience in relevant tools like SQL(expert), Excel, R/Python
• Statistics: Strong knowledge of statistics
• Should able to do data scraping & Data mining
• Be self-driven, and show ability to deliver on ambiguous projects
• An ability and interest in working in a fast-paced, ambiguous and rapidly-changing environment
• Should have worked on Business Projects for an organization, Ex: customer acquisition, Customer retention.

Square Panda is a startup headquartered in Sunnyvale, CA with additional offices located in India 

and China. We are in a research based Ed-Tech space, focusing on children's early literacy. We 

have 3000+ schools under our belt and are proud to cater the needs of English Language 

development of 70,000+ kids worldwide. Our multisensory neuroscience research-based phonics 

learning system comes equipped with educational games to teach children many essential skills. 

With a curriculum that has been specially adapted for Indian schools and children, we strive to 

empower beginner learners through phonics awareness.

 

  Responsibilities 

o Lead the identification and execution of opportunities where Analytics can make a difference across the company with focus on multiple markets we operate in - US, India and China.

 o Actively champion adoption of the analytics solutions across various markets and functions

 o Translate business problems into Insights projects and lead in quantifying the various types of risk and rewards that allow these projects to be prioritized.

 o Excellent project management and executive communication skills.

 o Understanding of the techniques and technologies of data science, along with a detailed understanding of the challenges associated with each (e.g. overfitting, model refresh, challenge of acquiring training data, cost of compute, etc.)

 o Proactively and continuously assess the marketplace and its dynamics, customers, and competitors. 

o Provide an unbiased point of view on the performance of markets/brands, supported by facts and evidence

 o Develop research strategies to ensure internal understanding of customer and competitor insights 

o Develop and implement market research & analytical plans, in collaboration with cross‐functional teams.

 o Seeks out alternative/creative ways of meeting an information need, considering new techniques to address business challenges.

 o Monitor program risks and ensure appropriate actions are taken, including escalating issues timely to the management 

o Maintain understanding of business operations and how users interact with the relevant systems and use that understanding to provide decision support analysis.

 o Tap the working knowledge of AI and analytics to convey these business goals to the data professionals who will create the models and solutions. 

o Enthusiasm, commitment, and business savvy to navigate the technical, political, and organizational roadblocks that can emerge.

 

 Desired Profile 

o 6-8 years of experience in executing multiple analytics projects end to end

 o Entrepreneurial mind-set o Should have played hands on data sciences role in the past with full knowledge of which analytics technique to apply 

o Background of core consulting / start up handling end to end projects o Excellent communication and project management skills o Ability to lead both business and analytics team to generate ROI and success for business o Expertise across the spectrum of analytics - Dashboards, Visualizations, Insights, Data Science driven AI, ML Projects  

1 to 3 years of experience in product analytics - Highly conversant with Google Analytics and other similar tools - Basic programming ability(preferably R or Python)

About the job: - You will work with data scientists to architect, code and deploy ML models - You will solve problems of storing and analyzing large scale data in milliseconds - architect and develop data processing and warehouse systems - You will code, drink, breathe and live python, sklearn and pandas. It’s good to have experience in these but not a necessity - as long as you’re super comfortable in a language of your choice. - You will develop tools and products that provide analysts ready access to the data About you: - Strong CS fundamentals - You have strong experience in working with production environments - You write code that is clean, readable and tested - Instead of doing it second time, you automate it - You have worked with some of the commonly used databases and computing frameworks (Psql, S3, Hadoop, Hive, Presto, Spark, etc) - It will be great if you have one of the following to share - a kaggle or a github profile - You are an expert in one or more programming languages (Python preferred). Also good to have experience with python-based application development and data science libraries. - Ideally, you have 2+ years of experience in tech and/or data. - Degree in CS/Maths from Tier-1 institutes.

RESPONSIBILITIES AND QUALIFICATIONS The mission of the Marcus Surveillance Analytics team is to deliver a platform which detects security incidents which have a tangible business impact and actionable response. You will work alongside industry leading technologists from who have recently joined Goldman from across consumer security, technology, fintech, finance and quant firms. The role has a broad scope which will involve interacting with senior leaders of Goldman and the Consumer business on a regular basis. The position is hands-on and requires a driven and “take ownership” oriented individual who is intently focused on execution. You will work directly with developers, business leaders, vendors and partners in order to deliver security assets to the consumer business. Develop a team, vision and platform which identifies/prioritizes actionable security & fraud risks which have tangible businesses impact across Goldman's consumer and commercial banking businesses. Develop response and recovery technology and programs to ensure resilience from fraud and abuse events. Manage, develop and operationalize analytics which discover security & fraud events and identifies risks for all of Goldman's consumer businesses. Partner with fraud / abuse operations and leadership to ensure consumer fraud rates are within industry norms and own outcomes related to fraud improvements. Skills And Experience We Are Looking For BA/BS degree in Computer Science, Cybersecurity, or other relevant Computer/Data/Engineering degrees 2+ years of experience as a security professional or data analyst/scientist/engineer Python, PySpark, R, Bash, SQL, Splunk (search, ES, UBA) Experience with cloud infrastructure/big data tool sets Visualization tools such as Tableau or D3 Research and development to create innovative predictive detections for security and fraud Build a 24/7 real-time monitoring system with long term vision for scaling to new lines of consumer businesses Strong focus on customer experience and product usability Ability to work closely with the business, fraud, and security incident response teams on creating actionable detections

The Candidate should be have: - good understanding of Statistical concepts - worked on Data Analysis and Model building for 1 year - ability to implement Data warehouse and Visualisation tools (IBM, Amazon or Tableau) - use of ETL tools - understanding of scoring models The candidate will be required: - to build models for approval or rejection of loans - build various reports (standard for monthly reporting) to optimise business - implement datawarehosue The candidate should be self-starter as well as work without supervision. You will be the 1st and only employee for this role for the next 6 months.