8+ Logistic regression Jobs in India

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

  Strong knowledge in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc. 

 Sound Knowlegde querying databases and using statistical computer languages: R, Python, SQL, etc. 

 Strong understanding creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. 

• 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

• 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:

• 1+ 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

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 is looking for a Data / Sr. Data Scientist who has the knowledge and experience in developing machine learning algorithms, particularly in supply chain and forecasting domain with data science toolkits like Python.

In this role, you will design the approach, develop and test machine learning algorithms, implement the solution.  The candidate should have excellent communication skills and be results driven with a customer centric approach to problem solving.  Experience working in the demand forecasting or supply chain domain is a plus. This job also requires the ability to operate in a multi-geographic delivery environment and a good understanding of cross-cultural sensitivities.

Responsibilities:

Responsibilities includes, but are not limited to the following:

• Design, build, test, and implement predictive Machine Learning models.
• Collaborate with client to align business requirements with data science systems and process solutions that ensure client’s overall objectives are met.
• Create meaningful presentations and analysis that tell a “story” focused on insights, to communicate the results/ideas to key decision makers.
• Collaborate cross-functionally with domain experts to identify gaps and structural problems.
• Contribute to standard business processes and practices as part of a community of practise.
• Be the subject matter expert across multiple work streams and clients.
• Mentor and coach team members.
• Set a clear vision for the team members and working cohesively to attain it.

Qualifications and Skills:

Requirements

• Experience / Education:
  • Master’s or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Applied Mathematics or other related 
• 5+ years’ experience working in applied machine learning or relevant research experience for recent Ph.D. graduates.
• Highly technical:
• Skilled in machine learning, problem-solving, pattern recognition and predictive modeling with expertise in PySpark and Python.
• Understanding of data structures and data modeling.
• Effective communication and presentation skills
• Able to collaborate closely and effectively with teams.
• Experience in time series forecasting is preferred.
• Experience working in start-up type environment preferred.
• Experience in CPG and/or Retail preferred.
• Effective communication and presentation skills.
• Strong management track record.
• Strong inter-personal skills and leadership qualities.

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