Industry Domain Lead – Retail/ CPG/ Insurance /Banking/ Automotive
About LatentView Analytics
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heads 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
- 3+ years experience in practical implementation and deployment of ML based systems preferred.
- BE/B Tech or M Tech (preferred) in CS/Engineering with strong mathematical/statistical background
- Strong mathematical and analytical skills, especially statistical and ML techniques, with familiarity with different supervised and unsupervised learning algorithms
- Implementation experiences and deep knowledge of Classification, Time Series Analysis, Pattern Recognition, Reinforcement Learning, Deep Learning, Dynamic Programming and Optimisation
- Experience in working on modeling graph structures related to spatiotemporal systems
- Programming skills in Python
- Experience in developing and deploying on cloud (AWS or Google or Azure)
- Good verbal and written communication skills
- Familiarity with well-known ML frameworks such as Pandas, Keras, TensorFlow
- 3+ years of industry experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka, ELK Stack, Fluentd and streaming databases like druid
- Strong industry expertise with containerization technologies including kubernetes, docker-compose
- 2+ years of industry in experience in developing scalable data ingestion processes and ETLs
- Experience with cloud platform services such as AWS, Azure or GCP especially with EKS, Managed Kafka
- Experience with scripting languages. Python experience highly desirable.
- 2+ Industry experience in python
- Experience with popular modern web frameworks such as Spring boot, Play framework, or Django
- Demonstrated expertise of building cloud native applications
- Experience in administering (including setting up, managing, monitoring) data processing pipelines (both streaming and batch) using frameworks such as Kafka, ELK Stack, Fluentd
- Experience in API development using Swagger
- Strong expertise with containerization technologies including kubernetes, docker-compose
- Experience with cloud platform services such as AWS, Azure or GCP.
- Implementing automated testing platforms and unit tests
- Proficient understanding of code versioning tools, such as Git
- Familiarity with continuous integration, Jenkins
- Design and Implement Large scale data processing pipelines using Kafka, Fluentd and Druid
- Assist in dev ops operations
- Develop data ingestion processes and ETLs
- Design and Implement APIs
- Assist in dev ops operations
- Identify performance bottlenecks and bugs, and devise solutions to these problems
- Help maintain code quality, organization, and documentation
- Communicate with stakeholders regarding various aspects of solution.
- Mentor team members on best practices
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Possess strong domain knowledge - Digital Analytics (Google Analytics, App Analytics (Firebase/AppsFlyer/Branch/MixPanel), CRO, Media Analytics
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Ability to handle Google Analytics clients end-to-end
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Contribute to building effective process management, mentoring teammates, reducing product & execution inefficiencies
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Be responsible for day-to-day Google Analytics operations and performance of client accounts, requiring interaction with both internal and external stakeholders.
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Own, manage and grow digital analytics strategies for clients.
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Be responsible for all regular (and ad hoc) reporting and analysis of digital activity providing crucial insights, and effectively communicating this to the client.
Almost a decade old, it is a venture committed to bring together a varied range of traditional crafts and techniques of dyeing, weaving, printing and hand embroidery. The founders have dedicated their life to promote Indian Block Prints and provide employment and Hand-Embroidery training to women so that numerous underprivileged women can be empowered.
What you will do:
- Developing analytical solutions to solve problem, identifying internal and external data, using analytical techniques including use of statistical techniques to analyse the problem, distilling information into actionable insights
- Participating in key decision-making forums and communicating key insights in an effective and influential manner
- Partnering with key stakeholders prioritizing analytics roadmap, demonstrating sense of urgency to identify and acting on opportunity and driving transparency on the work roadmap
- Monitoring and measuring launched initiatives [A/B testing] and feed learnings back into development process
- Managing multiple project priorities, deadlines and deliverables including rapid response as well as strategic priorities
- Identifying the appropriate data sources and building data assets to be able to enrich data and expand analytics capabilities
- Converting frequently asked questions into reports/ diagnostic tools
What you need to have:
- Graduate/ Post-Graduate Degree in Engineering, Mathematics, Statistics
- 8+ year of well-rounded analytics experience, preferably in internet B2C- Retail
- Strong exposure to data, analytical framework, hypothesis-based problem solving and scaling analytics
- Ability to work independently and drive your own projects
- Strong problem-solving skills
- Ability to translate business problem to analytics
- Expertise in data wrangling using SQL, exposure to Python is a plus
- Hands-on experience in using excel and power point
- Excellent communication skills
- Entrepreneurial mind-set, strong interpersonal skills
- Strong collaboration skills - inter and intra team
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
DataWeave 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.