Machine Learning Engineer

Data Scientist-

We are looking for an experienced Data Scientists to join our engineering team and

help us enhance our mobile application with data. In this role, we're looking for

people who are passionate about developing ML/AI in various domains that solves

enterprise problems. We are keen on hiring someone who loves working in fast paced start-up environment and looking to solve some challenging engineering

problems.

As one of the earliest members in engineering, you will have the flexibility to design

the models and architecture from ground up. As any early-stage start-up, we expect

you to be comfortable wearing various hats, and be proactive contributor in building

something truly remarkable.

Responsibilities

Researches, develops and maintains machine learning and statistical models for

business requirements

Work across the spectrum of statistical modelling including supervised,

unsupervised, & deep learning techniques to apply the right level of solution to

the right problem Coordinate with different functional teams to monitor outcomes and refine/

improve the machine learning models Implements models to uncover patterns and predictions creating business value and innovation

Identify unexplored data opportunities for the business to unlock and maximize

the potential of digital data within the organization

Develop NLP concepts and algorithms to classify and summarize structured/unstructured text data

Qualifications

3+ years of experience solving complex business problems using machine

learning.

Fluency in programming languages such as Python, NLP and Bert, is a must

Strong analytical and critical thinking skills

Experience in building production quality models using state-of-the-art technologies 

Familiarity with databases like MySQL, Oracle, SQL Server, NoSQL, etc. is

desirable Ability to collaborate on projects and work independently when required.

Previous experience in Fintech/payments domain is a bonus

You should have Bachelor’s or Master’s degree in Computer Science, Statistics

or Mathematics or another quantitative field from a top tier Institute

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

Data Scientist

Cubera is a data company revolutionizing big data analytics and Adtech through data share value principles wherein the users entrust their data to us. We refine the art of understanding, processing, extracting, and evaluating the data that is entrusted to us. We are a gateway for brands to increase their lead efficiency as the world moves towards web3.

What you’ll do?

• Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation, and serving.
• Research new and innovative machine learning approaches.
• Perform hands-on analysis and modeling of enormous data sets to develop insights that increase Ad Traffic and Campaign Efficacy.
• Collaborate with other data scientists, data engineers, product managers, and business stakeholders to build well-crafted, pragmatic data products.  
• Actively take on new projects and constantly try to improve the existing models and infrastructure necessary for offline and online experimentation and iteration.
• Work with your team on ambiguous problem areas in existing or new ML initiatives

What are we looking for?

• Ability to write a SQL query to pull the data you need.
• Fluency in Python and familiarity with its scientific stack such as numpy, pandas, scikit learn, matplotlib.
• Experience in Tensorflow and/or R Modelling and/or PyTorch
• Ability to understand a business problem and translate, and structure it into a data science problem. 

Job Category: Data Science

Job Type: Full Time

Job Location: Bangalore

Job description:

• Selecting features, building and optimizing classifiers using machine learning techniques
• Mining data as and when required
• Enhancing data collection procedures to include information that is relevant for building analytic systems
• Processing, cleansing, and verifying the integrity of data used for analysis
• Doing ad-hoc analysis and presenting results in a clear manner
• Creating automated anomaly detection systems and constant tracking of its performance
• Efficient stakeholder management

Skills and Qualifications

• Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Experience with common data science toolkits. 
• Great communication skills
• Experience with data visualisation tools
• Proficiency in using query languages such as SQL
• Good scripting and programming skills 
• Data-oriented personality
• B.Tech, M.Tech, B.S., M.S., MBA 

Requirement / Desired Skills

Data Scientist --  Data mining skills , SQL, Advanced ML Techniques, NLP (natural Language Processing)

1. Create and maintain optimal data pipeline architecture
2. Assemble large, complex data sets that meet business requirements
3. Identifying, designing, and implementing internal process improvements including redesigning infrastructure for greater scalability, optimizing data delivery, and automating manual processes
4. Work with Data, Analytics & Tech team to extract, arrange and analyze data
5. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS technologies
6. Building analytical tools to utilize the data pipeline, providing actionable insight into key business performance metrics including operational efficiency and customer acquisition
7. Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
8. Working with stakeholders including data, design, product, and executive teams, and assisting them with data-related technical issues
9. Working with stakeholders including the Executive, Product, Data, and Design teams to support their data infrastructure needs while assisting with data-related technical issues.

1. SQL
2. Ruby or Python(Ruby preferred)
3. Apache-Hadoop based analytics
4. Data warehousing
5. Data architecture
6. Schema design
7. ML

1.  Prior experience of 2 to 5 years as a Data Engineer.
2. Ability in managing and communicating data warehouse plans to internal teams.
3. Experience designing, building, and maintaining data processing systems.
4. Ability to perform root cause analysis on external and internal processes and data to identify opportunities for improvement and answer questions.
5. Excellent analytic skills associated with working on unstructured datasets.
6. Ability to build processes that support data transformation, workload management, data structures, dependency, and metadata.

• Required to work individually or as part of a team on data science projects and work closely with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions.
• Build quick prototypes to check feasibility and value to the business.
• Design, training, and deploying neural networks for computer vision and machine learning-related problems.
• Perform various complex activities related to statistical/machine learning.
• Coordinate with business teams to provide analytical support for developing, evaluating, implementing, monitoring, and executing models.
• Collaborate with technology teams to deploy the models to production.

Key Criteria:

• 2+ years of experience in solving complex business problems using machine learning.
• Understanding and modeling experience in supervised, unsupervised, and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required.
• Experience in Computer Vision/Image Processing/Pattern Recognition, Machine Learning, Deep Learning, or Artificial Intelligence.
• Understanding of Deep Learning Architectures like InceptionNet, VGGNet, FaceNet, YOLO, SSD, RCNN, MASK Rcnn, ResNet.
• Experience with one or more deep learning frameworks e.g., TensorFlow, PyTorch.
• Knowledge of vector algebra, statistical and probabilistic modeling is desirable.
• Proficiency in programming skills involving Python, C/C++, and Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython).
• Experience working with Amazon SageMaker or Azure ML Studio for deployments is a plus.
• Experience in data visualization software such as Tableau, ELK, etc is a plus.
• Strong analytical, critical thinking, and problem-solving skills.

• B.E/ B.Tech./ M. E/ M. Tech in Computer Science, Applied Mathematics, Statistics, Data Science, or related Engineering field.
• Minimum 60% in Graduation or Post-Graduation
• Great interpersonal and communication skills