Head Data Science

Job Description 

Data scientist with strong background in data mining, machine learning, recommendation systems, and statistics. Should possess signature strengths of a qualified mathematician with ability to apply concepts of Mathematics, Applied Statistics, with specialization in one or more of NLP, Computer Vision, Speech, Data mining to develop models that provide effective solution.. A strong data engineering background with hands-on coding capabilities is needed to own and deliver outcomes. 

A Master’s or PhD Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience, 7+ years of industry experience in predictive modelling, data science and analysis, with prior experience in a ML or data scientist role and a track record of building ML or DL models. 

Responsibilities and skills: 

● Work with our customers to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization. 

● Selecting features, building and optimizing classifiers using ML techniques ● Data mining using state-of-the-art methods, create text mining pipelines to clean & process large unstructured datasets to reveal high quality information and hidden insights using machine learning techniques 

● Should be able to appreciate and work on Computer Vision problems – for example extract rich information from images to categorize and process visual data— Develop machine learning algorithms for object and image classification, Experience in using DBScan, PCA, Random Forests and Multinomial Logistic Regression to select the best features to classify objects. 

OR 

● Deep understanding of NLP such as fundamentals of information retrieval, deep learning approaches, transformers, attention models, text summarisation, attribute extraction, etc. Preferable experience in one or more of the following areas: recommender systems, moderation of user generated content, sentiment analysis, etc. 

OR 

● Speech recognition, speech to text and vice versa, understanding NLP and IR, text summarisation, statistical and deep learning approaches to text processing. Experience of having worked in these areas.

Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Needs to appreciate deep learning frameworks like MXNet, Caffe 2, Keras, Tensorflow 

● Experience in working with GPUs to develop models, handling terabyte size datasets ● Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, mlr, mllib, Scikit-learn, caret etc - excellence in at least one of these is highly desirable ● Should be able to work hands-on in Python, R etc. Should closely collaborate & work with engineering teams to iteratively analyse data using Scala, Spark, Hadoop, Kafka, Storm etc., 

● Experience with NoSQL databases and familiarity with data visualization tools will be of great advantage

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

Role : 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.

 http://www.altimetrik.com/">http://www.altimetrik.com

https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end">https://www.youtube.com/watch?v=3nUs4YxppNE&;feature=emb_rel_end

https://www.youtube.com/watch?v=e40r6kJdC8c">https://www.youtube.com/watch?v=e40r6kJdC8c

Responsibilities:

• Identify relevant data sources - a combination of data sources to make it useful.
• Build the automation of the collection processes.
• Pre-processing of structured and unstructured data.
• Handle large amounts of information to create the input to analytical Models.
• Build predictive models and machine-learning algorithms Innovate Machine-Learning , Deep-Learning algorithms.
• Build Network graphs , NLP , Forecasting Models Building data pipelines for end-to-end solutions.
• Propose solutions and strategies to business challenges. Collaborate with product development teams and communicate with the Senior Leadership teams.
• Participate in Problem solving sessions

Requirements:

• Bachelor's degree in a highly quantitative field (e.g. Computer Science , Engineering , Physics , Math , Operations Research , etc) or equivalent experience.
• Extensive machine learning and algorithmic background with a deep level understanding of at least one of the following areas: supervised and unsupervised learning methods , reinforcement learning , deep learning , Bayesian inference , Network graphs , Natural Language Processing Analytical mind and business acumen
• Strong math skills (e.g. statistics , algebra)
• Problem-solving aptitude Excellent communication skills with ability to communicate technical information.
• Fluency with at least one data science/analytics programming language (e.g. Python , R , Julia).
• Start-up experience is a plus Ideally 5-8 years of advanced analytics experience in startups/marquee com

Required Skills:

Machine Learning, Deep Learning, Algorithms, Computer Science, Engineering, Operations Research, Math Skills, Communication Skills, SAAS Product, IT Services, Artificial Intelligence, ERP, Product Management, Automation, Analytical Models, Predictive Models, NLP, Forecasting Models, Product Development, Leadership, Problem Solving, Unsupervised Learning, Reinforcement Learning, Natural Language Processing, Algebra, Data Science, Programming Language, Python, Julia

Basic Qualifications:

• Five+ years experience working in a Big Data Software Development role
• Experience managing and deploying ML models in real world environments
• Bachelor's degree in Computer Science, Mathematics, Statistics, or other analytical fields
• Experience working with Python, Scala, 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

• Manages the delivery of large, complex Data Science projects using appropriate frameworks and collaborating with stake holders to manage scope and risk. Help the AI/ML Solution
• Analyst to build solution as per customer need on our platform Newgen AI Cloud. Drives profitability and continued success by managing service quality and cost and leading delivery. Proactively support sales through innovative solutions and delivery excellence.
•  

What you need to have: