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Risk Analytics - Manager / Sr.Manager :
> Risk Analytics, PD Model, Risk based Pricing Model, Portfolio & Collection Analytics, EWS
> Defining policies for different-2 partners, Credit Automation, Rule Engine Configuration, Credit Bureau Understanding
> Predictive Modelling, Segmentation, Clustering & ML Techniques, Python, Power BI
> Storytel ...ling, Structural Thinking, Problem Solver
> B.Tech, MBA, Statistics, Work Ex: 3-4 Yrs.
Who should Apply ?
> Who have productionized at least 2 models and seen challenges, success and failure cycle of the model implementation
> Not a strong believer of Fancy / complex algorithm rather focused of business value
> Can educate the senior management about the business value of an analytical solution rather techniques > Candidate with No / Less online certifications
> Candidate with Non-Premier Institute
> Candidate who have lost their job due to pandemicMore
Current state assessment of EDW, BI, Customer Experience initiatives of a bank to understand current pain points and recommend 3 years strategy and roadmap to address the pain points.
It involves understanding of pain points across various dimensions such as business requirements, end user experience, software engineering processes, tools & ...technologies, and architecture in place.
- Prior experience of doing similar assessments for banks.
- Experience of Design and Implementation of Enterprise Data warehouse, Business Intelligence, customer MDM.
- Exposure to Big Data, Machine Learning and Cognitive Solutions.
- Technical Skills include Teradata MDM & CIM, Microsoft SQL Server, SSIS, SSRS, SSAS, Power BI, Azure Data Factory, Data Lake, Machine Learning and Cognitive Services
Duration: 8 weeks
An experienced python developer, well versed in productionalizing solutions using the Flask/Dash framework, is who we are looking for.
Prior experience working with html/css, NoSQL databases like Redis, docker and integrating such solutions with relational databases will also be necessary in this role. Other required skillsets revolve around networking fundamentals, User experience, Git ...and windows/linux shell scripting is also mandatory for this role.
Prior experience working with Retail is an added bonus, alongside credible credentials around deploying similar solutions in the real world will be preferredMore
This task involves creating MS Access Database Forms based on the provided Word Doc templates.
In order to do this the candidate will need to :
* understand the existing database structure
* understand existing business rules and relationships
My organisation is an Australian based charity named "Palmera ", which created sustainable incomes for rural farmers in ...Sri Lanka. Palmera works with its partners based in Sri Lanka. Those partners collect data on paper in the local language and enter in english language MS Access Database. The database is then sent from Sri Lanka to the Palmera team in Sydeny,. The data is analysed and them uploaded into SQL/Power BI for performance analysis.
This process is working well.
The Access Forms which now need to be built are brand new, but need to follow the convention established in existing forms.
Seeking a BioStatistician with experience in Nutrition / Food Research to wokr on a Quantitative analysis project for a client.
Project Duration - 20 days
Experience in Nutrition / Food Research is a must !...
· Design and develop production NLP microservices.
· Stay current on the most recent NLP paradigms and design principles.
· Write documentation and test suites, and help maintain several codebases.
· & ...nbsp; Degree in computer science, information technology, or related field.
· Passion for building high quality production code.
· 3+ years relevant industry experience in production Python development.
· Should have good understanding of modern cloud technologies including micro-services, containerization, and SQL + NoSQL.
· Experience with NLP libraries and technologies including Spacy, PyTorch & Deep Learning models (eg: BERT) is a plus.
· Strong communication skills and an enthusiasm for working in an interdisciplinary and fast paced environment.More
Roles and responsibilities
? The Data Scientist is expected to have deep knowledge and skills in Machine Learning / Statistical Modelling / Big Data domain, and be responsible for the solution designing and project management for multiple projects/accounts
? Design the solution for advanced analytics (including Big Data) projects ? what technique to use, what tool/technology to use, etc ...r>? Scope out the solution in terms of time, effort, team skills needed independently
? Own the delivery for projects including developing scalable ML models and algorithms and interpreting the output
? Discuss various opportunities with existing and potential clients at a technical level
? Lead the effort on developing new capabilities/offerings/solutions across the firm
? Relevant experience of 6 8 years in advanced machine learning, advanced analytical modelling and optimization across multiple industries
? Expert level working knowledge of Python full stack (back end, analysis layer, implementation)
? Proficient in the analysis of both structured, unstructured data (text, image, video), and streaming (sensor) data;
? Working knowledge of deep learning; experience of having executed very large neural network based solutions
? Atleast 2+ years of Big Data experience including managing a Spark/HDFS based project
? Business domain and solutions knowledge of multiple industries, especially Retail, CPG, Telecom, etc.
? Good knowledge of various data visualization tools, especially open source such as D3, Gephi
? Excellent communication and client engagement skills
? Team management experience is a plus
? Master?s Degree in Computer Science / Mathematical Computing / Statistics / Operations Research
? At least 5 years? experience in Machine learning, Python, Big Data
Identification of Heading and Heading Levels from HTML files...
Quant Analyst (Analysis)
Energy markets are extremely dynamic. Therefore, our professionals in Wholesale trade 24 hours a day, 7 days a week to optimize portfolio returns and to mitigate market risks. Our focus is maximizing the extrinsic value of our assets (power plants, long-term contracts, gas pipelines and storage facilities, etc. ...) with our asset-backed trading strategy. In addition, we maximize profits through origination (structured deals) and proprietary trading activities. Furthermore, by supplying electricity and gas to B2B customers.
The Analytics department forms the ?competitive back-bone? wholesale activities. The importance of analytical competences and advanced quantitative methods and techniques has increased significantly in the last years due to the growing complexity of markets, assets and products. Also, the emergence of ?big data?, the very dynamic and rapidly changing energy market and the further internationalization of the playing field has boosted the demand for complex models and analysis. Market intelligence and analysis is not only central to the daily trading and asset optimization activities, but also in the introduction of new business models and in deciding among the difficult strategic alternatives with which energy companies are currently confronted. At the Analysis department everything is about ?brain power? and ?research & development?, but in a very results-oriented and commercial wholesale/trading environment. This demands a unique combination of analytical and commercial/entrepreneurial competences and people that can work both, independently and as a team, with an open and proactive attitude.
Analyse and quantify (very complex) market developments making visible the shifts in demand and supply through the use of mathematical and econometric models.
Actively search for market opportunities and translate them, through quantitative methods and techniques, into success factors and trading strategies for the Asset Book and trading books.
Build pricing models using Python and/or Matlab by simulating the price product and its drivers using Monte-Carlo techniques.
Interact with Structurers and Originators to price non-standard contracts.
Build asset hedging and asset optimization models.
What do we expect from you?
Qualifications, or working and intellectual level
Strong academic background (MSc or PhD ) in Econometrics or any other quantitative discipline
Knowledge, experience and skills in the specialist field
- Extensive knowledge in the field of quantitative models, methods and techniques.
- Thorough knowledge of (systematic) energy trading, complex energy contracts (structured products) and financial products (derivatives).
- Experience in pricing Structured Energy products.
- Experience building pricing models.
- Sound knowledge of the Electricity Imbalance System and the Day-ahead market. % More
1) Wordpress 2) Thinkific 3) Zoho Marketing hub, CRM, Page sense, Social, Subscriptions, books and analytics 4) Google - Ads, analytics, G-suite, Tag manager, Search Console 5) Facebook & LinkedIn (posting, ads, pixels/insights)
What I really need is to build some smart dashboards that help in more cl ...arity on the source of traffic and factors contributing to conversions. Will need help of folks who have experience and understanding of marketing analytics and are hands on in getting dashboards etc created. More
As a member of the Data Team, you will develop the data-driven solutions needed for the numeric transformation of Decathlon
- Build Cloud Data Pipeline : Design, build, test and deploy cutting edge analytics pipeline at Decathlon Sports India
- Data Ingestion : Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL ... and Big data technologies
- Data Integrity : Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognise and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
- Productionization : Productionization of AI-ML models using Restful API?s Framework & process management, Dockerization, CI-CD etc.
- Software Engineering : Work across all phases of SDLC, and use Software Engineering principles to build scaled solutions. Object-oriented languages (e.g. Python, R, Java, C#, C++ ) and frameworks (e.g. J2EE or .NET)
- Monitor existing solutions to ensure a good level of reliability.
- Organize support to quickly meet the needs of internal users.
- Continuously improve existing solutions.
- Anticipate the impacts of the release of other technical teams on the operation of current solutions.
- Be aware and test the new data-science methodologies / tools.
- Enlighten the possibilities and improve the clarity of data-science in the company.
- Collaborate and share learnings with the international network of data-scientists.
- Be proactive and challenge the vision of solutions.
- An expert capable of interpreting abstract data, apply mathematical algorithms on them to solve real-world problems.
- Expert in prototyping traditional ML (GBMs, scikit, etc.) and AI frameworks (keras, tensorflow, mxnet, pytorch, etc.) for a variety of applications.
- A clear and concise communicator, whether written or spoken.
- Trained in a technical ...field with a B.S. degree in Computer Science, Math, Machine Learning, or similar field.
Must have skills
- 12+ years of overall experience.
- Machine Learning / Data Science
- Linear regression, Logistic regression, Decision Tree, Random Forest & KNN
- Data Science, Statistical modelling, Predictive Modelling, ML and Modelling Tools
- Deep Learning
- Google Cloud is good to have if no good experience with Azure or AWS
As our Data Scientist, you will develop complex statistical models and machine learning algorithms to tackle critical product and business challenges. Working with the Product team, you will implement data science models that integrate into live production systems. Through deep behavioral analytics, you will yield significant product insights to help enhance our player experien ...ces. As a leader, you will level up our data science infrastructure and tools by contributing directly to our data intelligence vision and stack.
- Derive insights from data and present them to relevant stakeholders to improve business KPIs.
- Select features and build and optimize classifiers using machine learning techniques.
- Propose hypotheses and design experiments in the context of specific problems.
- Mine data using state-of-the-art techniques.
- Extend the company?s data with third-party sources of information when needed.
- Find opportunities to automate analytics and data flow processes using machine learning algorithms, and work with the Technical team to save time and increase productivity.
- Process and cleanse data, and verify the integrity of data used for analysis.
- Conduct ad hoc analysis and present results in a clear manner.
- Create automated anomaly detection systems and constantly track their performance.
- 6+ years of experience in a Data Scientist role, with hands-on experience in all stages and processes of data science, including statistical model development, machine learning, analytics and data operations.
- Ability to yield clear, actionable insights that improve business KPIs.
- Advanced applied statistics skills, such as distributions, statistical testing, regression, etc.
- Expertise in identifying trends, patterns, and outliers in data.
- Experience in statistical programming languages using analytical packages/library: R, Python.
- Experience in data visualization tools, such as Tableau, ClickView, and PowerBI.
- Experience in enterprise data technologies, large-scale DB management, ETL pipelines, and streaming models. Proficiency in SQL and relational databases, data warehousing, and NoSQL databases.
- Experience in Hadoop, PIG, and HIVE preferred, though not mandatory.
- Experience in machine learning: data/text mining, NLP, decision trees, adaptive decision algorithms, random forest and search algorithms.
- Data-oriented thinking and scientific temperament that seeks to rigorously validate hypotheses/ideas.
- Must have a Ph.D. in Statistics/Optimization Algorithms/Artificial Intelligence/Machine Learning, or a similar domain.
About Junglee Games
Junglee Games is a leader in the skill-gaming space, with over 25 million users. Founded in San Francisco in 2012, and funded by top-tier Silicon Valley VCs, Junglee Games is the fastest-growing skill-gaming company in the world. Some of our notable games are Junglee Rummy, Eatme.io, Junglee Teen Patti, and Howzat.
With teams in 7 countries, Junglee is 250 people strong and has close to doubled in revenues and headcount every year. With YOY growth of 80-100% and high pro?tability, Junglee will see close to $600 million in gross transaction volumes in FY19-20 and scale to 50 million users.
Our team has worked on international AAA titles like Transformers, Real Steel, Mech Conquest, and Dueling Blades. Our designers have worked on some of Hollyw More
Looking for an individual who has experience in the Insurance/Banking sector as an underwriter and can work on building scorecards that can help assess the risk levels of farmers at a macro level....
The data science team at WyngCommerce is on a mission to challenge the norms and re-imagine how retail business should be run across the world. As a Junior Data Scientist in the team, you will be driving and owning the thought leadership and impact on one of our core data science problems. You will work collaboratively with the founders, clients and engineering team to formulate complex problems, run Exploratory Data Analysis and test hypotheses, implement ML-based solutions and fine tune them with more data. This is a high impact role with goals that directly impact our business.
Your Role & Responsibilities:
- Implement data-driven solutions based on advanced ML and optimization algorithms to address business problems
- Research, experiment, and innovate ML/statistical approaches in various application areas of interest and contribute to IP
- Partner with engineering teams to build scalable, efficient, automated ML-based pipelines (training/evaluation/monitoring)
- Deploy, maintain, and debug ML/decision models in production environment
- Analyze and assess data to ensure high data quality and correctness of downstream processes
- Communicate results to stakeholders and present data/insights to participate in and drive decision making
Desired Skills & Experiences:
- Bachelors or Masters in a quantitative field from a top tier college
- 1-2 years experience in a data science / analytics role in a technology / analytics company
- Solid mathematical background (especially in linear algebra & probability theory)
- Familiarity with theoretical aspects of common ML techniques (generalized linear models, ensembles, SVMs, clustering algos, graphical models, etc.), statistical tests/metrics, experiment design, and evaluation methodologies
- Demonstrable track record of dealing with ambiguity, prioritizing needs, bias for iterative learning, and delivering results in a dynamic environment with minimal guidance
- Hands-on experience in at least one of the following: (a) Anomaly Detection, (b) Time Series Analysis, (c) Product Clustering, (d) Demand Forecasting, (e) Intertemporal Optimization
- Good programming skills (fluent in Java/Python/SQL) with experience of using common ML toolkits (e.g., sklearn, tensor flow, keras, nltk) to build models for real world problems
- Computational thinking and familiarity with practical application requirements (e.g., latency, memory, processing time)
- Excellent written and verbal communication skills for both technical and non-technical audiences
- (Plus Point) Experience of applying ML / other techniques in the domain of supply chain - and particularly in retail - for inventory optimization, demand forecasting, assortment planning, and other such problems
- (Nice to have) Research experience and publications in top ML/Data science conferences
You will be working with client relationship managers, product owners and developers to generate understanding, strategy and suggest actions based on data. You will be a blend of data hacker, business analyst, coder, communicator and guide to translate terabytesof data into customer insights or usable solutions.
Pro-actively identify opportunities for application of analytics in the organi ...zationUnderstand organization’s analytical needs and convert business problems to analytical problems
Take full ownership of your work, from the initial idea-generation phase to the implementation of the final product to its maintenance and improvement–Execute/deliver projects independently
Transform large complex datasets fromvarious sources (transactional, digital, logs, campaigns..)
Give pragmatic, actionable business /consumer insightsin a well-presented manner
Workwith cutting edge tools like GreenPlum, R, Python etc. and arriveat the best approach to solve challenging problems
Hands-on coding, data manipulation, integration plus deployment to production systems
Create marketing plans or campaign ideas and derive ideal target groups for campaigns based on various call to actions
Develop and automate Business Intelligence frameworks
Develop new algorithms for predicting or influencing consumer behavior prediction(eg: next purchase, attrition etc.)–Build, validate and deploy into production
Create client-ready decks for final deliverablesand present the same if needed
Develop and deploy solutions / algorithms for data qualitymonitoring and data enrichment
Mastering the fast evolving data structure and infrastructure; Understanding constraints and troubleshooting to arrive at workarounds when required
Work on end-to-end data management including database design, data update processes, datapipeline set-up and enriching data quality
Understand and experiment with different statistical and machine learning algorithms and apply them for business problems
Challenge ideas and methods while working together with talented, highly skilled team members.
Independently define & solveproblems,research & development, self-learning and skill development
Interview for recruitment and guide other members in the department
You will be working with client relationship managers, product owners and developers to generate understanding, strategy and suggest actions based on data. You will be a blend of data hacker, business analyst, coder, communicator and guide to translate terabytes of data into customer insights or usable solutions.
- Pro-actively identify opportunities for application of analytics in ... the organization
- Understand organization’s analytical needs and convert business problems to analytical problems
- Take full ownership of your work, from the initial idea-generation phase to the implementation of the final product to its maintenance and improvement – Execute/deliver projects independently
- Transform large complex datasets from various sources (transactional, digital, logs, campaigns..)
- Give pragmatic, actionable business / consumer insights in a well-presented manner
- Work with cutting edge tools like GreenPlum, R, Python etc. and arrive at the best approach to solve challenging problems
- Hands-on coding, data manipulation, integration plus deployment to production systems
- Create marketing plans or campaign ideas and derive ideal target groups for campaigns based on various call to actions
- Develop and automate Business Intelligence frameworks
- Develop new algorithms for predicting or influencing consumer behavior prediction (eg: next purchase, attrition etc.) – Build, validate and deploy into production
- Create client-ready decks for final deliverables and present the same if needed
- Develop and deploy solutions / algorithms for data quality monitoring and data enrichment
- Mastering the fast evolving data structure and infrastructure; Understanding constraints and troubleshooting to arrive at workarounds when required
- Work on end-to-end data management including database design, data update processes, data pipeline set-up and enriching data quality
- Understand and experiment with different statistical and machine learning algorithms and apply them for business problems
- Challenge ideas and methods while working together with talented, highly skilled team members.
- Independently define & solve problems, research & development, self-learning and skill development
- Interview for recruitment and guide other members in the department