Venus Factor Program

Analytical tool:  Redpoint 

• Research and drawing insights  
• Excellent written, oral and presentation skill  
• Critical thinking and problem-solving skill
• Applications: SQL, Redpoint  

Description:  

• Create unique fleet rich database using multi step matching rules  
• Critical thinking in identifying record survivor ship rules for identifying master record  
• Data roll-up at different levels, by providing linkage across databases  
• Learn issues clients are currently facing with their dataset  
• Foresee the problems in solving the issue during project planning based on historical work  
• Convert requirements into process flow. Customize & automate the process for upkeep  
• Helps clients identify their best Industry based on multiple KPIs’  
• Helps understand complete market, penetration level and available market  
• Identify core segments which can be penetrated with less effort.  
• Prioritize existing data to increase the penetration level
• Helps understand complete market, penetration level and available market  
• Identify core segments which can be penetrated with less effort.
• Prioritize existing data to increase the penetration level

Experience: 1- 5 Years

Job Location: WFH

No. of Position: Multiple

Qualifications: Ph.D. Must have

Work Timings: 1:30 PM IST to 10:30 PM IST

Functional Area: Data Science

NextGen Invent is currently searching for Data Scientist. This role will directly report to the VP, Data Science in Data Science Practice. The person will work on data science use-cases for the enterprise and must have deep expertise in supervised and unsupervised machine learning, modeling and algorithms with a strong focus on delivering use-cases and solutions at speed and scale to solve business problems.

Job Responsibilities:

• Leverage AI/ML modeling and algorithms to deliver on use cases
• Build modeling solutions at speed and scale to solve business problems
• Develop data science solutions that can be tested and deployed in Agile delivery model
• Implement and scale-up high-availability models and algorithms for various business and corporate functions
• Investigate and create experimental prototypes that work on specific domains and verticals
• Analyze large, complex data sets to reveal underlying patterns, and trends
• Support and enhance existing models to ensure better performance
• Set up and conduct large-scale experiments to test hypotheses and delivery of models

Skills, Knowledge, Experience:

• Must have Ph.D. in an analytical or technical field (e.g. applied mathematics, computer science)
• Strong knowledge of statistical and machine learning methods
• Hands on experience on building models at speed and scale
• Ability to work in a collaborative, transparent style with cross-functional stakeholders across the organization to lead and deliver results
• Strong skills in oral and written communication
• Ability to lead a high-functioning team and develop and train people
• Must have programming experience in SQL, Python and R
• Experience conceiving, implementing and continually improving machine learning projects
• Strong familiarity with higher level trends in artificial intelligence and open-source platforms
• Experience working with AWS, Azure, or similar cloud platform
• Familiarity with visualization techniques and software
• Healthcare experience is a plus
• Experience in Kafka, Chatbot and blockchain is a plus.

• Extremely good team player, with strong client/stakeholder management skills and line managerial skills.
• Complete working knowledge of Packaging Technology, Regulatory, Specification, Artwork Management, Mould Management, Rapid Prototyping, Packaging machineries & developmental process.
• Problem solving & bias for action mindset. Should have excellent communication skills and consumer & customer centricity.
• Advance project Management Skills, presentation skills& influencing skills.
• Good networking with Packaging material suppliers, IIP/SIES & other packaging testing laboratories & with Plastic waste management entities such as Producer Responsibility Organizations (PROs)& recyclers.
• Basic appreciation of product development principles.  

• Cross-functional coordination of digital marketing programs.
• Ability to convey the power of the company platform, by defining customer lifecycle journeys and assets to facilitate program execution.
• Engage our customers in a human, meaningful, and value-driven manner. Define and execute customer lifecycle adoption and engagement programs in accordance with digital strategy and execution plan.
• Leverage engagement capabilities to reach thousands of customers based on targeted, segmented approaches.
• Monitor and report on metrics associated with program execution.
• Ability to leverage data and analytics to expand and optimize programs.
• Accountability for adoption, renewal, and churn improvement goals.

Requirements

• 4+ years of industry experience; 2+ years in a related domain. Experience in successful multi-channel enterprise SaaS digital engagement and adoption programs is a strong plus.
• Bachelor’s degree; advanced degree in a business, marketing or technical field preferred.
• Demonstrate being data-driven: continuously test, measure, and improve programs and tactics.
• Possess expertise in the use of various content types and engagement methods, such as video, chat, social media, mobile, email to execute digital programs.
• Knowledge of Google Analytics / Gainsight / Marketo / Optimizely / Pendo / Salesforce / Tableau, etc. to get the data and insights you need to successfully design, execute and monitor programs.
• Prior experience as a customer lifecycle marketer, growth product manager/marketer, product marketing manager, or digital customer success manager.
• Excellent communication - verbal and written.
• Display effective leadership skills, team collaboration, and executive presentation skills

factorie.io is a digital manufacturing enterprise, connecting disparate data sources to align manufacturing activities in real time, substantially impacting manufacturing throughput. 

Operating in an inherently data-rich environment – we seek to be the source of real time intelligence for manufacturing operations by processing and elevating data from machines, ERP and other IT applications. 

The company is currently being led by four co-founders with a cumulative management, technology and manufacturing experience of more than 100 years. In place is a dedicated strategic consulting for manufacturers to transition to digital enterprise, ISV partners and pilot clients. As we work towards empowering manufacturers at scale, we are looking for a high caliber IIoT / embedded systems engineer to lead data acquisition from machines. This is a leadership position and you'll be a Co-founder of the Company. All Co-founders are compensated from founders' equity in the Company – and, cash compensation will commence only after completing 12 months association as Co-founder.

Nurtured as a product-based technology company, our Co-founder would be someone who considers himself to be a methodical hacker – energized by simply the process of building products that solve meaningful problems. You have a bias for action, taking consistent, incremental and measurable steps towards releases that serve the product’s immediate and long-term needs.

If that person is you, we look forward to experimenting and tinkering with the next generation of IoT and data analytics use cases – together. 

ASK YOURSELF IF YOU ARE: 

Entrepreneurial? Someone who believes it is their time to shine and is tired of operating in a manager's shadow. Have you started-up before – or, even thought about doing so? Tell us your story. 

A hands-on craftsman? Someone who loves to build, understands the architecture of complex software applications and frameworks. Do you contribute to opensource projects and / or have you developed / are you developing certain ‘hobby’ applications? We would love to know about them. Do you have an engineering blog we should be following? We are NOT accepting managers for this position, please. 

Disciplined, passionate and obsessive? Someone who needs to solve REAL problems that have potential network implications on how products are manufactured in the world today – democratizing the hitherto ‘privileged’ power of Industry 4.0.

THE SKILLS YOU NEED / TECHNOLOGIES WE’RE WORKING ON,

CORE:

• Experience of data acquisition, extraction and normalization from PLCs and sensors with open protocols (OPC-UA, Modbus and MTConnect) + proprietary connectors (for Siemens Sinumerik, Fanuc and Mitsubishi)

• Comfortable building the Edge hardware and software infrastructure - IoT Gateways, IoT Servers installed on Linux or Android (Yocto) forks

• Exposure to low latency connectivity architecture using a combination of Wireless (Cellular, Wi-Fi, Bluetooth, and NFC), and wired (Ethernet) interfaces. Consequently, necessary is an understanding of Profinet and MQTT communication standards.

• In depth knowledge of the architecture of smart manufacturing software components - SCADA, Historian, MES etc.

• Have leveraged a cross-section database types - RDS (Postgres) and / or NoSQL (MongoDB, DynamoDB)

• A fanatical level of thoroughness with the OOP such as C++, JAVA (Spring) as well as the more recent Node.js, Go 

FUNDAMENTALS:

• Strong CS fundamentals. Deep knowledge of math, probability, statistics and algorithms. Delivering full-stack projects from conceptualization to production. Iterating, developing and testing MVPs quickly - therefore identifying opportunities to automate the development cycle to the maximum feasible extent.

• Extensive experience of leveraging (opensource) libraries / solutions, frameworks, APIs, AWS IIoT (or similar) etc., to drive efficiencies in product development. We’re NOT planning to reinvent the wheel.

• Familiarity with deploying and developing in a microservices architecture. i.e., deploying on a containerized (Kubernetes, Docker, ECS, EKS etc.) stack that communicates via REST APIs. Developing while religiously following the CI / CD methodology.

• Trade tools such as PLC simulators, IoT device / sensor simulators, Cucumber, Selenium, GIT, IDEs (ex., Eclipse), JIRA etc., would be almost second nature