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Machine Learning (ML)
Data Science
Role: Head of Analytics
Location: Bangalore (Full time)
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ABOUT THE COMPANY WE ARE HIRING FOR:
Our client is offering credit card solutions for banks and financial institutions. It provides services like credit card design and onboarding, credit card authorization, payment processing, collections and dispute resolutions, credit card fraud detection, and more. They serve in the B2B space in the FinTech market segments.
POSITION OVERVIEW
We are seeking an experienced individual for the role of Head of Analytics. As the Head of Analytics, you will be responsible for driving data-driven decision-making, implementing advanced analytics strategies, and providing valuable insights to optimize our credit card business operations, sales and marketing, risk management & customer experience. Your expertise in statistical analysis, predictive modeling, and data visualization will be instrumental in driving growth and enhancing the overall performance of our credit card business.
Responsibilities:
1. Develop and implement Analytics Strategy:
o Define the analytics roadmap for the credit card business, aligning it with overall
business objectives.
o Identify key performance indicators (KPIs) and metrics to track the performance
of the credit card business.
o Collaborate with senior management and cross-functional teams to prioritize and
execute analytics initiatives. 2. Lead Data Analysis and Insights:
o Conduct in-depth analysis of credit card data, customer behavior, and market trends to identify opportunities for business growth and risk mitigation.
o Develop predictive models and algorithms to assess credit risk, customer segmentation, acquisition, retention, and upsell opportunities.
o Generate actionable insights and recommendations based on data analysis to optimize credit card product offerings, pricing, and marketing strategies.
o Regularly present findings and recommendations to senior leadership, using data visualization techniques to effectively communicate complex information.
3. Drive Data Governance and Quality:
o Oversee data governance initiatives, ensuring data accuracy, consistency, and
integrity across relevant systems and platforms.
o Collaborate with IT teams to optimize data collection, integration, and storage
processes to support advanced analytics capabilities.
o Establish and enforce data privacy and security protocols to comply with
regulatory requirements.
4. Team Leadership and Collaboration:
o Build and manage a high-performing analytics team, fostering a culture of innovation, collaboration, and continuous learning.
o Provide guidance and mentorship to the team, promoting professional growth and development.
o Collaborate with stakeholders across departments, including Marketing, Risk Management, and Finance, to align analytics initiatives with business objectives.
5. Stay Updated on Industry Trends:
o Keep abreast of emerging trends, techniques, and technologies in analytics, credit
card business, and the financial industry.
o Leverage industry best practices to drive innovation and continuous improvement
in analytics methodologies and tools.
Qualifications:
Bachelor's or master’s degree in Technology, Mathematics, Statistics, Economics, Computer Science, or a related field.
Proven experience (7+ years) in leading analytics teams in the credit card industry.
Strong expertise in statistical analysis, predictive modelling, data mining, and segmentation techniques.
Proficiency in data manipulation and analysis using programming languages such as Python, R, or SQL.
Experience with analytics tools such as SAS, SPSS, or Tableau.
Excellent leadership and team management skills, with a track record of building and developing high-performing teams.
Strong knowledge of credit card business and understanding of credit card industry dynamics, including risk management, marketing, and customer lifecycle.
Exceptional communication and presentation skills, with the ability to effectively communicate complex information to a varied audience.
Data ScienceMachine Learning (ML)As an Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve
predefined outcomes.
• Engage with clients to understand current and future business goals and translate business
problems into analytical frameworks
• Develop custom models based on an in-depth understanding of underlying data, data structures,
and business problems to ensure deliverables meet client needs
• Create repeatable, interpretable and scalable models
• Effectively communicate the analytics approach and insights to a larger business audience
• Collaborate with team members, peers and leadership at Tredence and client companies
Qualification:
1. Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics,
statistics) or equivalent experience.
2. 5+ years of experience in data science, building hands-on ML models
3. Experience leading the end-to-end design, development, and deployment of predictive
modeling solutions.
4. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data
analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc.
5. Advanced SQL skills with SQL Server and Spark experience.
6. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms
(Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
7. Experience with Natural Language Processing (NLTK) and text analytics for information
extraction, parsing and topic modeling.
8. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills.
Thrive in a fast-paced, innovative environment
9. Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred
10. Experience with cloud platforms such as Azure, AWS is preferred but not required
Data Science
R Programming
Python
MongoDB- Conducting advanced statistical analysis to provide actionable insights, identify trends, and measure performance
- Performing data exploration, cleaning, preparation and feature engineering; in addition to executing tasks such as building a POC, validation/ AB testing
- Collaborating with data engineers & architects to implement and deploy scalable solutions
- Communicating results to diverse audiences with effective writing and visualizations
- Identifying and executing on high impact projects, triage external requests, and ensure timely completion for the results to be useful
- Providing thought leadership by researching best practices, conducting experiments, and collaborating with industry leaders
What you need to have:
- 2-4 year experience in machine learning algorithms, predictive analytics, demand forecasting in real-world projects
- Strong statistical background in descriptive and inferential statistics, regression, forecasting techniques.
- Strong Programming background in Python (including packages like Tensorflow), R, D3.js , Tableau, Spark, SQL, MongoDB.
- Preferred exposure to Optimization & Meta-heuristic algorithm and related applications
- Background in a highly quantitative field like Data Science, Computer Science, Statistics, Applied Mathematics,Operations Research, Industrial Engineering, or similar fields.
- Should have 2-4 years of experience in Data Science algorithm design and implementation, data analysis in different applied problems.
- DS Mandatory skills : Python, R, SQL, Deep learning, predictive analysis, applied statistics
Deep LearningMachine Learning (ML)Introduction
Synapsica is a growth stage HealthTech startup founded by alumni from IIT Kharagpur, AIIMS New Delhi, and IIM Ahmedabad. We believe healthcare needs to be transparent and objective, while being affordable. Every patient has the right to know exactly what is happening in their bodies and they don’t have to rely on cryptic 2 liners given to them as diagnosis. Towards this aim, we are building an artificial intelligence enabled cloud based platform to analyse medical images and create v2.0 of advanced radiology reporting. We are backed by YCombinator and other investors from India, US and Japan. We are proud to have GE, AIIMS, and the Spinal Kinetics as our partners.
Your Roles and Responsibilities
The role involves computer vision tasks including development, customization and training of Convolutional Neural Networks (CNNs); application of ML techniques (SVM, regression, clustering etc.) and traditional Image Processing (OpenCV etc.). The role is research focused and would involve going through and implementing existing research papers, deep dive of problem analysis, generating new ideas, automating and optimizing key processes.
Requirements:
- Strong problem-solving ability
- Prior experience with Python, cuDNN, Tensorflow, PyTorch, Keras, Caffe (or similar Deep Learning frameworks).
- Extensive understanding of computer vision/image processing applications like object classification, segmentation, object detection etc
- Ability to write custom Convolutional Neural Network Architecture in Pytorch (or similar)
- Experience of GPU/DSP/other Multi-core architecture programming
- Effective communication with other project members and project stakeholders
- Detail-oriented, eager to learn, acquire new skills
- Prior Project Management and Team Leadership experience
- Ability to plan work and meet deadlines
- End to end deployment of deep learning models.
PythonMongoDB- Experience with relational SQL & NoSQL databases including MySQL & MongoDB.
- Familiar with the basic principles of distributed computing and data modeling.
- Experience with distributed data pipeline frameworks like Celery, Apache Airflow, etc.
- Experience with NLP and NER models is a bonus.
- Experience building reusable code and libraries for future use.
- Experience building REST APIs.
Preference for candidates working in tech product companies
Data ScienceR ProgrammingPythonculture and operating norms as a result of the fast-paced nature of a new, high-growth
organization.
• 7+ years of Industry experience primarily related to Unstructured Text Data and NLP
(PhD work and internships will be considered if they are related to unstructured text
in lieu of industry experience but not more than 2 years will be accounted towards
industry experience)
• Develop Natural Language Medical/Healthcare documents comprehension related
products to support Health business objectives, products and improve
processing efficiency, reducing overall healthcare costs
• Gather external data sets; build synthetic data and label data sets as per the needs
for NLP/NLR/NLU
• Apply expert software engineering skills to build Natural Language products to
improve automation and improve user experiences leveraging unstructured data storage, Entity Recognition, POS Tagging, ontologies, taxonomies, data mining,
information retrieval techniques, machine learning approach, distributed and cloud
computing platforms
• Own the Natural Language and Text Mining products — from platforms to systems
for model training, versioning, deploying, storage and testing models with creating
real time feedback loops to fully automated services
• Work closely and collaborate with Data Scientists, Machine Learning engineers, IT
teams and Business stakeholders spread out across various locations in US and India
to achieve business goals
• Provide mentoring to other Data Scientist and Machine Learning Engineers
• Strong understanding of mathematical concepts including but not limited to linear
algebra, Advanced calculus, partial differential equations and statistics including
Bayesian approaches
• Strong programming experience including understanding of concepts in data
structures, algorithms, compression techniques, high performance computing,
distributed computing, and various computer architecture
• Good understanding and experience with traditional data science approaches like
sampling techniques, feature engineering, classification and regressions, SVM, trees,
model evaluations
• Additional course work, projects, research participation and/or publications in
Natural Language processing, reasoning and understanding, information retrieval,
text mining, search, computational linguistics, ontologies, semantics
• Experience with developing and deploying products in production with experience
in two or more of the following languages (Python, C++, Java, Scala)
• Strong Unix/Linux background and experience with at least one of the following
cloud vendors like AWS, Azure, and Google for 2+ years
• Hands on experience with one or more of high-performance computing and
distributed computing like Spark, Dask, Hadoop, CUDA distributed GPU (2+ years)
• Thorough understanding of deep learning architectures and hands on experience
with one or more frameworks like tensorflow, pytorch, keras (2+ years)
• Hands on experience with libraries and tools like Spacy, NLTK, Stanford core NLP,
Genism, johnsnowlabs for 5+ years
• Understanding business use cases and be able to translate them to team with a
vision on how to implement
• Identify enhancements and build best practices that can help to improve the
productivity of the team.
Machine Learning (ML)- Key Responsibilities : Use cases to support use case analysis E2E, define capabilities, understand the data and model Machine Learning Operations MLOps Azure Machine Learning, Azure Cognitive Services, Azure DevOps, Overall Azure Cloud Experience, Powershell, DSVM, AML Compute / Training Clusters Azure Infrastructure Experience, Python, Big Data Python Scripting 8 Automate ML models deployments, Manage, monitor, troubleshoot machine learning infrastructure and Setup ML Pipe lines
- Technical Experience : Proven skills experience in Azure AI ML solution design and architecture based solution using Azure Cloud capabilities AML / AKS Proven record of embedding advanced analytical models into business processes Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle teams analytics problems and communicate results bitbucket, Nodejs, PowerBI SQL, Python
- Experience in setting up MLOps framework for AI ML team
PythonMachine Learning (ML)Deep LearningData ScienceR ProgrammingPythonMachine Learning (ML)
Data SciencePythonMachine Learning (ML)
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