Data Scientist

About antuit.ai

Antuit.ai is the leader in AI-powered SaaS solutions for Demand Forecasting & Planning, Merchandising and Pricing. We have the industry’s first solution portfolio – powered by Artificial Intelligence and Machine Learning – that can help you digitally transform your Forecasting, Assortment, Pricing, and Personalization solutions. World-class retailers and consumer goods manufacturers leverage antuit.ai solutions, at scale, to drive outsized business results globally with higher sales, margin and sell-through.

Antuit.ai’s executives, comprised of industry leaders from McKinsey, Accenture, IBM, and SAS, and our team of Ph.Ds., data scientists, technologists, and domain experts, are passionate about delivering real value to our clients. Antuit.ai is funded by Goldman Sachs and Zodius Capital.

The Role:

Antuit.ai is interested in hiring a Principal Data Scientist, this person will facilitate standing up standardization and automation ecosystem for ML product delivery, he will also actively participate in managing implementation, design and tuning of product to meet business needs.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Manage and provides technical expertise to the delivery team. This includes recommendation of solution alternatives, identification of risks and managing business expectations.
• Design, build reliable and scalable automated processes for large scale machine learning.
• Use engineering expertise to help design solutions to novel problems in software development, data engineering, and machine learning. 
• Collaborate with Business, Technology and Product teams to stand-up MLOps process.
• Apply your experience in making intelligent, forward-thinking, technical decisions to delivery ML ecosystem, including implementing new standards, architecture design, and workflows tools.
• Deep dive into complex algorithmic and product issues in production
• Own metrics and reporting for delivery team. 
• Set a clear vision for the team members and working cohesively to attain it.
• Mentor and coach team members

Qualifications and Skills:

Requirements

• Engineering degree in any stream
• Has at least 7 years of prior experience in building ML driven products/solutions
• Excellent programming skills in any one of the language C++ or Python or Java.
• Hands on experience on open source libraries and frameworks- Tensorflow,Pytorch, MLFlow, KubeFlow, etc.
• Developed and productized large-scale models/algorithms in prior experience
• Can drive fast prototypes/proof of concept in evaluating various technology, frameworks/performance benchmarks.
• Familiar with software development practices/pipelines (DevOps- Kubernetes, docker containers, CI/CD tools).
• Good verbal, written and presentation skills.
• Ability to learn new skills and technologies.
• 3+ years working with retail or CPG preferred.
• Experience in forecasting and optimization problems, particularly in the CPG / Retail industry preferred.

Information Security Responsibilities

• Understand and adhere to Information Security policies, guidelines and procedure, practice them for protection of organizational data and Information System.
• Take part in Information Security training and act accordingly while handling information.
• Report all suspected security and policy breach to Infosec team or appropriate authority (CISO).

EEOC

The role is with a Fintech Credit Card company based in Pune within the Decision Science team. (OneCard )

About

Credit cards haven't changed much for over half a century so our team of seasoned bankers, technologists, and designers set out to redefine the credit card for you - the consumer. The result is OneCard - a credit card reimagined for the mobile generation. OneCard is India's best metal credit card built with full-stack tech. It is backed by the principles of simplicity, transparency, and giving back control to the user.

The Engineering Challenge

“Re-imaging credit and payments from First Principles”

Payments is an interesting engineering challenge in itself with requirements of low latency, transactional guarantees, security, and high scalability. When we add credit and engagement into the mix, the challenge becomes even more interesting with underwriting and recommendation algorithms working on large data sets. We have eliminated the current call center, sales agent, and SMS-based processes with a mobile app that puts the customers in complete control. To stay agile, the entire stack is built on the cloud with modern technologies.

Purpose of Role :

- Develop and implement the collection analytics and strategy function for the credit cards. Use analysis and customer insights to develop optimum strategy.

CANDIDATE PROFILE :

- Successful candidates will have in-depth knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques. They will be an adept communicator with good interpersonal skills to work with senior stake holders in India to grow revenue primarily through identifying / delivering / creating new, profitable analytics solutions.

We are looking for someone who:

- Proven track record in collection and risk analytics preferably in Indian BFSI industry. This is a must.

- Identify & deliver appropriate analytics solutions

- Experienced in Analytics team management

Essential Duties and Responsibilities :

- Responsible for delivering high quality analytical and value added services

- Responsible for automating insights and proactive actions on them to mitigate collection Risk.

- Work closely with the internal team members to deliver the solution

- Engage Business/Technical Consultants and delivery teams appropriately so that there is a shared understanding and agreement as to deliver proposed solution

- Use analysis and customer insights to develop value propositions for customers

- Maintain and enhance the suite of suitable analytics products.

- Actively seek to share knowledge within the team

- Share findings with peers from other teams and management where required

- Actively contribute to setting best practice processes.

Knowledge, Experience and Qualifications :

Knowledge :

- Good understanding of collection analytics preferably in Retail lending industry.

- Knowledge of statistical modelling/data analysis tools (Python, R etc.), techniques and market trends

- Knowledge of different modelling frameworks like Linear Regression, Logistic Regression, Multiple Regression, LOGIT, PROBIT, time- series modelling, CHAID, CART etc.

- Knowledge of Machine learning & AI algorithms such as Gradient Boost, KNN, etc.

- Understanding of decisioning and portfolio management in banking and financial services would be added advantage

- Understanding of credit bureau would be an added advantage

Experience :

- 4 to 8 years of work experience in core analytics function of a large bank / consulting firm.

- Experience on working on Collection analytics is must

- Experience on handling large data volumes using data analysis tools and generating good data insights

- Demonstrated ability to communicate ideas and analysis results effectively both verbally and in writing to technical and non-technical audiences

- Excellent communication, presentation and writing skills Strong interpersonal skills

- Motivated to meet and exceed stretch targets

- Ability to make the right judgments in the face of complexity and uncertainty

- Excellent relationship and networking skills across our different business and geographies

Qualifications :

- Masters degree in Statistics, Mathematics, Economics, Business Management or Engineering from a reputed college

Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.

What will you do?

• You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
• You will be constantly assessing and improving the model using techniques like Transfer learning
• You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
• You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
• Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
• Building predictive models and machine-learning algorithms to apply to data sets.
• Coordinate with different functional teams to implement models and monitor outcomes.
•  
• Presenting information using data visualization techniques and proposing solutions and strategies to business challenges

We would love to hear from you if :

• You have 2+ years of experience as a software engineer at a SaaS or technology company
• Demonstrable hands-on programming experience with Python/R Data Science Stack
• Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
• Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
• Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
• Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
• Preferable Experience Experienced in web crawling and data scraping
• Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
• Experience with text mining, pattern matching and fuzzy matching

• Brand new Macbook
• Stock Options
• Health Insurance
• Unlimited Sick Leaves
• Passion Fund (Invest in yourself or your passion project)
• Wind Down

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.

• Use data to develop machine learning models that optimize decision making in Credit Risk, Fraud, Marketing, and Operations
• Implement data pipelines, new features, and algorithms that are critical to our production models
• Create scalable strategies to deploy and execute your models
• Write well designed, testable, efficient code
• Identify valuable data sources and automate collection processes.
• Undertake to preprocess of structured and unstructured data.
• Analyze large amounts of information to discover trends and patterns.

Requirements:

• 2+ years of experience in applied data science or engineering with a focus on machine learning
• Python expertise with good knowledge of machine learning libraries, tools, techniques, and frameworks (e.g. pandas, sklearn, xgboost, lightgbm, logistic regression, random forest classifier, gradient boosting regressor, etc)
• strong quantitative and programming skills with a product-driven sensibility

Responsibilities

• Own the design, development, testing, deployment, and craftsmanship of the team’s infrastructure and systems capable of handling massive amounts of requests with high reliability and scalability
• Leverage the deep and broad technical expertise to mentor engineers and provide leadership on resolving complex technology issues
• Entrepreneurial and out-of-box thinking essential for a technology startup
• Guide the team for unit-test code for robustness, including edge cases, usability, and general reliability

Requirements

• In-depth understanding of image processing algorithms, pattern recognition methods, and rule-based classifiers
• Experience in feature extraction, object recognition and tracking, image registration, noise reduction, image calibration, and correction
• Ability to understand, optimize and debug imaging algorithms
• Understating and experience in openCV library
• Fundamental understanding of mathematical techniques involved in ML and DL schemas (Instance-based methods, Boosting methods, PGM, Neural Networks etc.)
• Thorough understanding of state-of-the-art DL concepts (Sequence modeling, Attention, Convolution etc.) along with knack to imagine new schemas that work for the given data.
• Understanding of engineering principles and a clear understanding of data structures and algorithms
• Experience in writing production level codes using either C++ or Java
• Experience with technologies/libraries such as python pandas, numpy, scipy
• Experience with tensorflow and scikit.