- Work closely with your business to identify issues and use data to propose solutions for effective decision making
- Build algorithms and design experiments to merge, manage, interrogate and extract data to supply tailored reports to colleagues, customers or the wider organisation.
- Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc
- Querying databases and using statistical computer languages: R, Python, SLQ, etc.
- Visualizing/presenting data through various Dashboards for Data Analysis, Using Python Dash, Flask etc.
- Test data mining models to select the most appropriate ones for use on a project
- Work in a POSIX/UNIX environment to run/deploy applications
- Mine and analyze data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
- 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.
- Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
- Horizon scan to stay up to date with the latest technology, techniques and methods
- Coordinate with different functional teams to implement models and monitor outcomes.
- Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work.
General Expectations:
- Able to create algorithms to extract information from large data sets
- Strong knowledge of Python, R, Java or another scripting/statistical languages to automate data retrieval, manipulation and analysis.
- Experience with extracting and aggregating data from large data sets using SQL or other tools
- Strong understanding of various NLP, and NLU techniques like Named Entity Recognition, Summarization, Topic Modeling, Text Classification, Lemmatization and Stemming.
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, etc.
- Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
- Experience with Jupyter / Pandas / Numpy to manipulate and analyse data
- Knowledge of Machine Learning techniques and their respective pros and cons
- Strong Knowledge of various Data Science Visualization Tools like Tableau, PowerBI, D3, Plotly, etc.
- Experience using web services: Redshift, AWS, S3, Spark, DigitalOcean, etc.
- Proficiency in using query languages, such as SQL, Spark DataFrame API, etc.
- Hands-on experience in HTML, CSS, Bootstrap, JavaScript, AJAX, jQuery and Prototyping.
- Hands-on experience on C#, Javascript, .Net
- Experience in understanding and analyzing data using statistical software (e.g., Python, R, KDB+ and other relevant libraries)
- Experienced in building applications that meet enterprise needs – secure, scalable, loosely coupled design
- Strong knowledge of computer science, algorithms, and design patterns
- Strong oral and written communication, and other soft skills critical to collaborating and engage with teams
About Archcorp Architectural Engineering
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Skills: Machine Learning,Deep Learning,Artificial Intelligence,python.
Location:Chennai
Domain knowledge: Data cleaning, modelling, analytics, statistics, machine learning, AI
Requirements:
· To be part of Digital Manufacturing and Industrie 4.0 projects across Saint Gobain group of companies
· Design and develop AI//ML models to be deployed across SG factories
· Knowledge on Hadoop, Apache Spark, MapReduce, Scala, Python programming, SQL and NoSQL databases is required
· Should be strong in statistics, data analysis, data modelling, machine learning techniques and Neural Networks
· Prior experience in developing AI and ML models is required
· Experience with data from the Manufacturing Industry would be a plus
Roles and Responsibilities:
· Develop AI and ML models for the Manufacturing Industry with a focus on Energy, Asset Performance Optimization and Logistics
· Multitasking, good communication necessary
· Entrepreneurial attitude.
Principal Accountabilities :
1. Good in communication and converting business requirements to functional requirements
2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data
3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.
5. Experience in SOTA Deep Learning techniques to solve NLP problems.
6. End-to-end data collection, model development and testing, and integration into production environments.
7. Build and prototype analysis pipelines iteratively to provide insights at scale.
8. Experience in querying different data sources
9. Partner with developers and business teams for the business-oriented decisions
10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.
● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypothesis through theoretical and empirical approaches.
● Productize proven or working models into production quality code.
● Collaborate with product management, marketing and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision makers.
● File patents for innovative solutions that add to company's IP portfolio
Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/PhD in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes (only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Expertise in Python programming language and fluency in analytical tools
such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis
● Strong communication and collaboration skills.
What you will do:
- Identifying alternate data sources beyond financial statements and implementing them as a part of assessment criteria
- Automating appraisal mechanisms for all newly launched products and revisiting the same for an existing product
- Back-testing investment appraisal models at regular intervals to improve the same
- Complementing appraisals with portfolio data analysis and portfolio monitoring at regular intervals
- Working closely with the business and the technology team to ensure the portfolio is performing as per internal benchmarks and that relevant checks are put in place at various stages of the investment lifecycle
- Identifying relevant sub-sector criteria to score and rate investment opportunities internally
Desired Candidate Profile
What you need to have:
- Bachelor’s degree with relevant work experience of at least 3 years with CA/MBA (mandatory)
- Experience in working in lending/investing fintech (mandatory)
- Strong Excel skills (mandatory)
- Previous experience in credit rating or credit scoring or investment analysis (preferred)
- Prior exposure to working on data-led models on payment gateways or accounting systems (preferred)
- Proficiency in data analysis (preferred)
- Good verbal and written skills
- Working closely with business stakeholders to define, strategize and execute crucial business problem statements which lie at the core of improvising current and future data-backed product offerings.
- Building and refining underwriting models for extending credit to sellers and API Partners in collaboration with the lending team
- Conceiving, planning and prioritizing data projects and manage timelines
- Building analytical systems and predictive models as a part of the agile ecosystem
- Testing performance of data-driven products participating in sprint-wise feature releases
- Managing a team of data scientists and data engineers to develop, train and test predictive models
- Managing collaboration with internal and external stakeholders
- Building data-centric culture from within, partnering with every team, learning deeply about business, working with highly experienced, sharp and insanely ambitious colleagues
What you need to have:
- B.Tech/ M.Tech/ MS/ PhD in Data Science / Computer Science, Statistics, Mathematics & Computation with a demonstrated skill-set in leading an Analytics and Data Science team from IIT, BITS Pilani, ISI
- 8+ years working in the Data Science and analytics domain with 3+ years of experience in leading a data science team to understand the projects to be prioritized, how the team strategy aligns with the organization mission;
- Deep understanding of credit risk landscape; should have built or maintained underwriting models for unsecured lending products
- Should have handled a leadership team in a tech startup preferably a fintech/ lending/ credit risk startup.
- We value entrepreneurship spirit: if you have had the experience of starting your own venture - that is an added advantage.
- Strategic thinker with agility and endurance
- Aware of the latest industry trends in Data Science and Analytics with respect to Fintech, Digital Transformations and Credit-lending domain
- Excellent command over communication is the key to manage multiple stakeholders like the leadership team, product teams, existing & new investors.
- Cloud Computing, Python, SQL, ML algorithms, Analytics and problem - solving mindset
- Knowledge and demonstrated skill-sets in AWS
We are looking for a Data Scientist who is excited by the prospects of Mining Big Datasets, Deriving Actionable Insights, Building production-ready Predictive Models and have a direct impact on business.
RESPONSIBILITIES:
- Hands-on knowledge of Python for building production-ready data products.
- Strong Statistical Analysis and Modeling skills.
- Proven skills in Data Science, Data Mining, Machine Learning, covering the spectrum of supervised as well as unsupervised learning algorithms.
- Ability to grasp and work with new technologies quickly.
- Knowledge of Reinforcement Learning is a plus.
- Some knowledge of big data technologies like Hadoop, Apache Spark will be an added advantage
QUALIFICATION REQUIRED:
- Bachelor’s or Master's degree in STEM.
- 3-7 years of relevant experience in applied Data Science.
@ ONLINESALES.AI:
- Get a chance to work with some of the most popular big data technologies in the market
- Build algorithms that work on web-scale data
- Participate in every aspect of building a data-based product
- Chance of making a dent in a multi-billion dollar digital advertising industry
YOU CAN BE A GREAT FIT IF YOU HAVE:
- An analytical approach towards problem-solving
- Experience with data extraction and management
- Experience with R, Python for Data Analysis and Data modeling.
- Ability to set goals and meet deadlines in a fast-paced working environment
- Understanding of E-Commerce and Advertising as a domain.
- Willingness to work for a startup.
- Individual Contributor with a sense of Business Acumen and a hunger to make an impact.
● Frame ML / AI use cases that can improve the company’s product
● Implement and develop ML / AI / Data driven rule based algorithms as software items
● For example, building a chatbot that replies an answer from relevant FAQ, and
reinforcing the system with a feedback loop so that the bot improves
Must have skills:
● Data extraction and ETL
● Python (numpy, pandas, comfortable with OOP)
● Django
● Knowledge of basic Machine Learning / Deep Learning / AI algorithms and ability to
implement them
● Good understanding of SDLC
● Deployed ML / AI model in a mobile / web product
● Soft skills : Strong communication skills & Critical thinking ability
Good to have:
● Full stack development experience
Required Qualification:
B.Tech. / B.E. degree in Computer Science or equivalent software engineering
Responsibilities:
- The Machine & Deep Machine Learning Software Engineer (Expertise in Computer Vision) will be an early member of a growing team with responsibilities for designing and developing highly scalable machine learning solutions that impact many areas of our business.
- The individual in this role will help in the design and development of Neural Network (especially Convolution Neural Networks) & ML solutions based on our reference architecture which is underpinned by big data & cloud technology, micro-service architecture and high performing compute infrastructure.
- Typical daily activities include contributing to all phases of algorithm development including ideation, prototyping, design, and development production implementation.
Required Skills:
- An ideal candidate will have a background in software engineering and data science with expertise in machine learning algorithms, statistical analysis tools, and distributed systems.
- Experience in building machine learning applications, and broad knowledge of machine learning APIs, tools, and open-source libraries
- Strong coding skills and fundamentals in data structures, predictive modeling, and big data concepts
- Experience in designing full stack ML solutions in a distributed computing environment
- Experience working with Python, Tensor Flow, Kera’s, Sci-kit, pandas, NumPy, AZURE, AWS GPU
- Excellent communication skills with multiple levels of the organization
- Image CNN, Image processing, MRCNN, FRCNN experience is a must.