11+ Statistical Modeling Jobs in Bangalore (Bengaluru) | Statistical Modeling Job openings in Bangalore (Bengaluru)
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Data Science
Python
Machine Learning (ML)Data Science:
• Python expert level, Analytical, Different models works, Basic concepts, CPG(Domain).
• Statistical Models & Hypothesis , Testing
• Machine Learning Important
• Business Understanding, visualization in Python.
• Classification, clustering and regression
•
Mandatory Skills
• Data Science, Python, Machine Learning, Statistical Models, Classification, clustering and regression
PythonResponsibilities
This role requires a person to support business charters & accompanying products by aligning with the Analytics
Manager’s vision, understanding tactical requirements and helping in successful execution. Split would be approx.
70% management + 30% individual contributor. Responsibilities include
Project Management
- Understand business needs and objectives.
- Refine use cases and plan iterations and deliverables - able to pivot as required.
- Estimate efforts and conduct regular task updates to ensure timeline adherence.
- Set and manage stakeholder expectations as required
Quality Execution
- Help BA and SBA resources with requirement gathering and final presentations.
- Resolve blockers regarding technical challenges and decision-making.
- Check final deliverables for correctness and review codes, along with Manager.
KPIs and metrics
- Orchestrate metrics building, maintenance, and performance monitoring.
- Owns and manages data models, data sources, and data definition repo.
- Makes low-level design choices during execution.
Team Nurturing
- Help Analytics Manager during regular one-on-ones + check-ins + recruitment.
- Provide technical guidance whenever required.
- Improve benchmarking and decision-making skills at execution-level.
- Train and get new resources up-to-speed.
- Knowledge building (methodologies) to better position the team for complex problems.
Communication
- Upstream to document and discuss execution challenges, process inefficiencies, and feedback loops.
- Downstream and parallel for context-building, mentoring, stakeholder management.
Analytics Stack
- Analytics : Python / R + SQL + Excel / PPT, Colab notebooks
- Database : PostgreSQL, Amazon Redshift, DynamoDB, Aerospike
- Warehouse : Amazon Redshift
- ETL : Lots of Python + custom-made
- Business Intelligence / Visualization : Metabase + Python/R libraries (location data)
- Deployment pipeline : Docker, Git, Jenkins, AWS Lambda
The role of a Personal Loan Risk Head is to own, manage and communicate risk policies and processes. He/She shall provide hands-on development of risk models involving market, credit and operational risk, assure controls are operating effectively, and provide research and analytical support. Prospective candidates must have excellent quantitative and analytical skills, along with the ability to apply those skills across a variety of business processes.
Key Expectations
- Designing and implementing an overall risk management process for the Personal Loan portfolio, which includes an analysis of the financial impact on the company when risks occur
- Performing a risk assessment: Analyzing current risks and identifying potential risks that are affecting the company
- Own the portfolio risk metrics - Loss forecasting, Stress testing, Credit Risk, Liquidity risk, Collections performance & strategy & overall ROA by segment.
- Monitor portfolio risk from granular dimensions and constantly implement strategies to maintain risk metrics within specific ranges.
- Monitor various operational metrics and develop alerting mechanisms to maintain process efficiency
- Designing and implementing strategies for Underwriting, Account Management, Portfolio Monitoring and Collections
- Develop risk based credit policies and pricing grids to maximize approvals within specific segments of risk
- Work with data science team which will develop algorithms and scorecards and drive decision models across various business segments.
- Partner with Engineering team to implement policies and scorecards.
- Supervise creation of time-sensitive analytics, visualisations, and complicated, high-visibility reports for Risk and Business management to use in portfolio monitoring and strategic decision-making.
Competencies -
- Have strong business understanding of the retail lending business in India and understanding of the regulatory landscape
- Should have hands-on experience working as data analyst or data scientist or statistical modeler in retail space, preferably in financial services or ecommerce.
- Strong experience in establishing and managing high-performing teams with a collaborative leadership approach.
- Outstanding communication skills, both verbal and written
Data Science● 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.
Data ScienceMachine Learning (ML)Pythonheads to solve complex business problems
- Develop statistical, and machine learning-based models/pipelines/methods to improve business
processes and engagements
- Conduct sophisticated data mining analyses of large volumes of data and build data science
models, as required, as part of the credit and risk underwriting solutions; customer engagement and
retention; new business initiatives; business process improvements
- Translate data mining results into a clear business-focused deliverable for decisionmakers
- Working with Application Developers on integrating machine learning algorithms and data mining
models into operational systems so it could lead to automation, productivity increase, and time
savings
- Provide the technical direction required to resolve complex issues to ensure the on-time delivery of
solutions that meet the business team’s expectations. May need to develop new methods to apply
to situations
- Knowledge of how to leverage statistical models in algorithms is a must
- Experience in multivariate analysis; identifying how several parameters can affect
retention/behaviour of the customer and identifying actions at different points of the customer lifecycle
Extensive experience coding in Python and having mentored teams to learn the same
- Great understanding of the data science landscape and what tools to leverage for different
problems
- A great structured thinker that could bring structure to any data science problem quickly
- Ability to visualize data stories and adept in data visualization tools and present insights as cohesive
stories to senior leadership
- Excellent capability to organize large data sets collected from many sources (web APIs and internal
databases) to get actionable insights
- Initiate data science programs in the team and collaborate across other data science teams to build
a knowledge database
Data SciencePythonRole : Sr Data Scientist / Tech Lead – Data Science
Number of positions : 8
Responsibilities
- Lead a team of data scientists, machine learning engineers and big data specialists
- Be the main point of contact for the customers
- Lead data mining and collection procedures
- Ensure data quality and integrity
- Interpret and analyze data problems
- Conceive, plan and prioritize data projects
- Build analytic systems and predictive models
- Test performance of data-driven products
- Visualize data and create reports
- Experiment with new models and techniques
- Align data projects with organizational goals
Requirements (please read carefully)
- Very strong in statistics fundamentals. Not all data is Big Data. The candidate should be able to derive statistical insights from very few data points if required, using traditional statistical methods.
- Msc-Statistics/ Phd.Statistics
- Education – no bar, but preferably from a Statistics academic background (eg MSc-Stats, MSc-Econometrics etc), given the first point
- Strong expertise in Python (any other statistical languages/tools like R, SAS, SPSS etc are just optional, but Python is absolutely essential). If the person is very strong in Python, but has almost nil knowledge in the other statistical tools, he/she will still be considered a good candidate for this role.
- Proven experience as a Data Scientist or similar role, for about 7-8 years
- Solid understanding of machine learning and AI concepts, especially wrt choice of apt candidate algorithms for a use case, and model evaluation.
- Good expertise in writing SQL queries (should not be dependent upon anyone else for pulling in data, joining them, data wrangling etc)
- Knowledge of data management and visualization techniques --- more from a Data Science perspective.
- Should be able to grasp business problems, ask the right questions to better understand the problem breadthwise /depthwise, design apt solutions, and explain that to the business stakeholders.
- Again, the last point above is extremely important --- should be able to identify solutions that can be explained to stakeholders, and furthermore, be able to present them in simple, direct language.
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Data Science
Deep LearningMachine Learning (ML)Responsibilities
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Building out and manage a young data science vertical within the organization
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Provide technical leadership in the areas of machine learning, analytics, and data sciences
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Work with the team and create a roadmap to solve the company’s requirements by solving data-mining, analytics, and ML problems by Identifying business problems that could be solved using Data Science and scoping it out end to end.
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Solve business problems by applying advanced Machine Learning algorithms and complex statistical models on large volumes of data.
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Develop heuristics, algorithms, and models to deanonymize entities on public blockchains
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Data Mining - Extend the organization’s proprietary dataset by introducing new data collection methods and by identifying new data sources.
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Keep track of the latest trends in cryptocurrency usage on open-web and dark-web and develop counter-measures to defeat concealment techniques used by criminal actors.
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Develop in-house algorithms to generate risk scores for blockchain transactions.
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Work with data engineers to implement the results of your work.
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Assemble large, complex data sets that meet functional / non-functional business requirements.
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Build, scale and deploy holistic data science products after successful prototyping.
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Clearly articulate and present recommendations to business partners, and influence future plans based on insights.
Preferred Experience
-
>8+ years of relevant experience as a Data Scientist or Analyst. A few years of work experience solving NLP problems or other ML problems is a plus
-
Must have previously managed a team of at least 5 data scientists or analysts or demonstrate that they have prior experience in scaling a data science function from the ground
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Good understanding of python, bash scripting, and basic cloud platform skills (on GCP or AWS)
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Excellent communication skills and analytical skills
What you’ll get
-
Work closely with the Founders in helping grow the organization to the next level alongside some of the best and brightest talents around you
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An excellent culture, we encourage collaboration, growth, and learning amongst the team
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Competitive salary and equity
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An autonomous and flexible role where you will be trusted with key tasks.
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An opportunity to have a real impact and be part of a company with purpose.
Role: Power BI Developer
Company: KOCH (https://www.kochind.com/" target="_blank">https://www.kochind.com)
Type: Permanent (Direct payroll)
Edu: Any Full time Graduates
Exp : 4+ Yrs
Job Location: Kundalahalli,Near Brookefield Hospital, Bangalore -560037
Job Description:
-
3+ years’ experience developing and implementing enterprise-scale reports and dashboards.
-
Proficiency with MS Power BI / SSRS.
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Knowledge of logical and physical data modeling concepts (relational and dimensional).
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Understanding of structured query language (SQL).
R Programming
Data AnalyticsThe person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.
At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain.
Candidates will be expected to lead projects across several areas such as
- Demand forecasting
- Inventory management
- Simulation & Mathematical optimization models.
- Procurement analytics
- Distribution/Logistics planning
- Network planning and optimization
Qualification and Experience
- 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain.
- Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain
- Hands-on experience in delivery of projects using statistical modelling
Skills / Knowledge
- Hands on experience in statistical modelling software such as R/ Python and SQL.
- Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage.
- Highly proficient with Excel, PowerPoint and Word applications.
- APICS-CSCP or PMP certification will be added advantage
- Strong knowledge of supply chain management
- Working knowledge on the linear/nonlinear optimization
- Ability to structure problems through a data driven decision-making process.
- Excellent project management skills, including time and risk management and project structuring.
- Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis.
- Ability to liaison effectively with multiple stakeholders and functional disciplines.
- Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.
Machine Learning (ML)PythonData ScienceDeep LearningDataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.
Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.
How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!
What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.
- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.
Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.
We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).
Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.
Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.
Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.
Data SciencePythonMachine Learning (ML)
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