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- 3-5yrs of practical DS experience working with varied data sets. Working with retail banking is preferred but not necessary.
- Need to be strong in concepts of statistical modelling – particularly looking for practical knowledge learnt from work experience (should be able to give "rule of thumb" answers)
- Strong problem solving skills and the ability to articulate really well.
- Ideally, the data scientist should have interfaced with data engineering and model deployment teams to bring models / solutions to "live" in production.
- Strong working knowledge of python ML stack is very important here.
- Willing to work on diverse range of tasks in building ML related capability on the Corridor Platform as well as client work.
- Someone with strong interest in data engineering aspect of ML is highly preferred, i.e. can play dual role of Data Scientist as well as someone who can code a module on our Corridor Platform writing robust code.
Structured ML techniques for candidates:
- GBM
- XgBoost
- Random Forest
- Neural Net
- Logistic Regression
DATA SCIENTIST-MACHINE LEARNING
GormalOne LLP. Mumbai IN
Job Description
GormalOne is a social impact Agri tech enterprise focused on farmer-centric projects. Our vision is to make farming highly profitable for the smallest farmer, thereby ensuring India's “Nutrition security”. Our mission is driven by the use of advanced technology. Our technology will be highly user-friendly, for the majority of farmers, who are digitally naive. We are looking for people, who are keen to use their skills to transform farmers' lives. You will join a highly energized and competent team that is working on advanced global technologies such as OCR, facial recognition, and AI-led disease prediction amongst others.
GormalOne is looking for a machine learning engineer to join. This collaborative yet dynamic, role is suited for candidates who enjoy the challenge of building, testing, and deploying end-to-end ML pipelines and incorporating ML Ops best practices across different technology stacks supporting a variety of use cases. We seek candidates who are curious not only about furthering their own knowledge of ML Ops best practices through hands-on experience but can simultaneously help uplift the knowledge of their colleagues.
Location: Bangalore
Roles & Responsibilities
- Individual contributor
- Developing and maintaining an end-to-end data science project
- Deploying scalable applications on different platform
- Ability to analyze and enhance the efficiency of existing products
What are we looking for?
- 3 to 5 Years of experience as a Data Scientist
- Skilled in Data Analysis, EDA, Model Building, and Analysis.
- Basic coding skills in Python
- Decent knowledge of Statistics
- Creating pipelines for ETL and ML models.
- Experience in the operationalization of ML models
- Good exposure to Deep Learning, ANN, DNN, CNN, RNN, and LSTM.
- Hands-on experience in Keras, PyTorch or Tensorflow
Basic Qualifications
- Tech/BE in Computer Science or Information Technology
- Certification in AI, ML, or Data Science is preferred.
- Master/Ph.D. in a relevant field is preferred.
Preferred Requirements
- Exp in tools and packages like Tensorflow, MLFlow, Airflow
- Exp in object detection techniques like YOLO
- Exposure to cloud technologies
- Operationalization of ML models
- Good understanding and exposure to MLOps
Kindly note: Salary shall be commensurate with qualifications and experience
We are looking for a Machine Learning engineer for on of our premium client.
Experience: 2-9 years
Location: Gurgaon/Bangalore
Tech Stack:
Python, PySpark, the Python Scientific Stack; MLFlow, Grafana, Prometheus for machine learning pipeline management and monitoring; SQL, Airflow, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS; Django, GraphQL and ReactJS for horizontal product development; container technologies such as Docker and Kubernetes, CircleCI/Jenkins for CI/CD, cloud solutions such as AWS, GCP, and Azure as well as Terraform and Cloudformation for deployment
1. ROLE AND RESPONSIBILITIES
1.1. Implement next generation intelligent data platform solutions that help build high performance distributed systems.
1.2. Proactively diagnose problems and envisage long term life of the product focusing on reusable, extensible components.
1.3. Ensure agile delivery processes.
1.4. Work collaboratively with stake holders including product and engineering teams.
1.5. Build best-practices in the engineering team.
2. PRIMARY SKILL REQUIRED
2.1. Having a 2-6 years of core software product development experience.
2.2. Experience of working with data-intensive projects, with a variety of technology stacks including different programming languages (Java,
Python, Scala)
2.3. Experience in building infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data
sources to support other teams to run pipelines/jobs/reports etc.
2.4. Experience in Open-source stack
2.5. Experiences of working with RDBMS databases, NoSQL Databases
2.6. Knowledge of enterprise data lakes, data analytics, reporting, in-memory data handling, etc.
2.7. Have core computer science academic background
2.8. Aspire to continue to pursue career in technical stream
3. Optional Skill Required:
3.1. Understanding of Big Data technologies and Machine learning/Deep learning
3.2. Understanding of diverse set of databases like MongoDB, Cassandra, Redshift, Postgres, etc.
3.3. Understanding of Cloud Platform: AWS, Azure, GCP, etc.
3.4. Experience in BFSI domain is a plus.
4. PREFERRED SKILLS
4.1. A Startup mentality: comfort with ambiguity, a willingness to test, learn and improve rapidl
- Banking Domain
- Assist the team in building Machine learning/AI/Analytics models on open-source stack using Python and the Azure cloud stack.
- Be part of the internal data science team at fragma data - that provides data science consultation to large organizations such as Banks, e-commerce Cos, Social Media companies etc on their scalable AI/ML needs on the cloud and help build POCs, and develop Production ready solutions.
- Candidates will be provided with opportunities for training and professional certifications on the job in these areas - Azure Machine learning services, Microsoft Customer Insights, Spark, Chatbots, DataBricks, NoSQL databases etc.
- Assist the team in conducting AI demos, talks, and workshops occasionally to large audiences of senior stakeholders in the industry.
- Work on large enterprise scale projects end-to-end, involving domain specific projects across banking, finance, ecommerce, social media etc.
- Keen interest to learn new technologies and latest developments and apply them to projects assigned.
Desired Skills |
- Professional Hands-on coding experience in python for over 1 year for Data scientist, and over 3 years for Sr Data Scientist.
- This is primarily a programming/development-
oriented role - hence strong programming skills in writing object-oriented and modular code in python and experience of pushing projects to production is important. - Strong foundational knowledge and professional experience in
- Machine learning, (Compulsory)
- Deep Learning (Compulsory)
- Strong knowledge of At least One of : Natural Language Processing or Computer Vision or Speech Processing or Business Analytics
- Understanding of Database technologies and SQL. (Compulsory)
- Knowledge of the following Frameworks:
- Scikit-learn (Compulsory)
- Keras/tensorflow/pytorch (At least one of these is Compulsory)
- API development in python for ML models (good to have)
- Excellent communication skills.
- Excellent communication skills are necessary to succeed in this role, as this is a role with high external visibility, and with multiple opportunities to present data science results to a large external audience that will include external VPs, Directors, CXOs etc.
- Hence communication skills will be a key consideration in the selection process.
- You'd have to set up your own shop, work with design customers to find generalizable use cases, and build them out.
- Ability to collaborate with cross-functional teams to build and ship new features
- At least 2-5 years of experience
- Predictive Analytics – Machine Learning Algorithms, Logistics & Linear Regression, Decision Tree, Clustering.
- Exploratory Data Analysis – Data Preparation, Data Exploration, and Data Visualization.
- Analytics Tools – R, Python, SQL, Power BI, MS Excel.
Glance – An InMobi Group Company:
Glance is an AI-first Screen Zero content discovery platform, and it’s scaled massively in the last few months to one of the largest platforms in India. Glance is a lock-screen first mobile content platform set up within InMobi. The average mobile phone user unlocks their phone >150 times a day. Glance aims to be there, providing visually rich, easy to consume content to entertain and inform mobile users - one unlock at a time. Glance is live on more than 80 millions of mobile phones in India already, and we are only getting started on this journey! We are now into phase 2 of the Glance story - we are going global!
Roposo is part of the Glance family. It is a short video entertainment platform. All the videos created here are user generated (via upload or Roposo creation tools in camera) and there are many communities creating these videos on various themes we call channels. Around 4 million videos are created every month on Roposo and power Roposo channels, some of the channels are - HaHa TV (for comedy videos), News, Beats (for singing/ dance performances) along with a For You (personalized for a user) and Your Feed (for videos of people a user follows).
What’s the Glance family like?
Consistently featured among the “Great Places to Work” in India since 2017, our culture is our true north, enabling us to think big, solve complex challenges and grow with new opportunities. Glanciers are passionate and driven, creative and fun-loving, take ownership and are results-focused. We invite you to free yourself, dream big and chase your passion.
What can we promise?
We offer an opportunity to have an immediate impact on the company and our products. The work that you shall do will be mission critical for Glance and will be critical for optimizing tech operations, working with highly capable and ambitious peer groups. At Glance, you get food for your body, soul, and mind with daily meals, gym, and yoga classes, cutting-edge training and tools, cocktails at drink cart Thursdays and fun at work on Funky Fridays. We even promise to let you bring your kids and pets to work.
What you will be doing?
Glance is looking for a Data Scientist who will design and develop processes and systems to analyze high volume, diverse "big data" sources using advanced mathematical, statistical, querying, and reporting methods. Will use machine learning techniques and statistical analysis to predict outcomes and behaviors. Interacts with business partners to identify questions for data analysis and experiments. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and or prepares output from analysis and experiments to business partners.
You will be working with Product leadership, taking high-level objectives and developing solutions that fulfil these requirements. Stakeholder management across Eng, Product and Business teams will be required.
Basic Qualifications:
- Five+ years experience working in a Data Science role
- Extensive experience developing and deploying ML models in real world environments
- Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
- Exceptional familiarity with Python, Java, Spark or other open-source software with data science libraries
- Experience in advanced math and statistics
- Excellent familiarity with command line linux environment
- Able to understand various data structures and common methods in data transformation
- Experience deploying machine learning models and measuring their impact
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.
Preferred Qualifications
- Experience developing recommendation systems
- Experience developing and deploying deep learning models
- Bachelor’s or Master's Degree or PhD that included coursework in statistics, machine learning or data analysis
- Five+ years experience working with Hadoop, a NoSQL Database or other big data infrastructure
- Experience with being actively engaged in data science or other research-oriented position
- You would be comfortable collaborating with cross-functional teams.
- Active personal GitHub account.
Mining large volumes of credit behavior data to generate insights around product holdings and monetization opportunities for cross sell
Use data science to size opportunity and product potential for launch of any new product/pilots
Build propensity models using heuristics and campaign performance to maximize efficiency.
Conduct portfolio analysis and establish key metrics for cross sell partnership
Desired profile/Skills:
2-5 years of experience with a degree in any quantitative discipline such as Engineering, Computer Science, Economics, Statistics or Mathematics
Excellent problem solving and comprehensive analytical skills – ability to structure ambiguous problem statements, perform detailed analysis and derive crisp insights.
Solid experience in using python and SQL
Prior work experience in a financial services space would be highly valued
Location: Bangalore/ Ahmedabad
at Artivatic
About us
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 a Master's degree and 1+ years of experience working on problems in NLP or Computer Vision.
If you have 4+ years of relevant experience with a Master's degree (PhD preferred), you will be considered for a senior role.
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.