Data Scientist

Role: Head of Analytics

Location: Bangalore (Full time)

ABOUT QRATA: 

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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. 

Key Responsibilities:

1. Collaborate with business stakeholders and data analysts to understand reporting requirements and translate them into effective Power BI solutions.
2. Design and develop interactive and visually compelling dashboards, reports, and visualizations using Microsoft Power BI.
3. Ensure data accuracy and consistency in the reports by working closely with data engineers and data architects.
4. Optimize and streamline existing Power BI reports and dashboards for better performance and user experience.
5. Develop and maintain data models and data connections to various data sources, ensuring seamless data integration.
6. Implement security measures and data access controls to protect sensitive information in Power BI reports.
7. Troubleshoot and resolve issues related to Power BI reports, data refresh, and connectivity problems.
8. Stay updated with the latest Power BI features and capabilities, and evaluate their potential use in improving existing solutions.
9. Conduct training sessions and workshops for end-users to promote self-service BI capabilities and enable them to create their own reports.
10. Collaborate with the wider data and analytics team to identify opportunities for using Power BI to enhance business processes and decision-making.

Requirements:

1. Bachelor's degree in Computer Science, Information Systems, or a related field.
2. Proven experience as a Power BI Developer or similar role, with a strong portfolio showcasing previous Power BI projects.
3. Proficient in Microsoft Power BI, DAX (Data Analysis Expressions), and M (Power Query) to manipulate and analyze data effectively.
4. Solid understanding of data visualization best practices and design principles to create engaging and intuitive dashboards.
5. Strong SQL skills and experience with data modeling and database design concepts.
6. Knowledge of data warehousing concepts and ETL (Extract, Transform, Load) processes.
7. Ability to work with various data sources, including relational databases, APIs, and cloud-based platforms.
8. Excellent problem-solving skills and a proactive approach to identifying and addressing issues in Power BI reports.
9. Familiarity with data security and governance practices in the context of Power BI development.
10. Strong communication and interpersonal skills to collaborate effectively with cross-functional teams and business stakeholders.
11. Experience with other BI tools (e.g., Tableau, QlikView) is a plus.

The role of a Power BI Developer is critical in enabling data-driven decision-making and empowering business users to gain valuable insights from data. The successful candidate will have a passion for data visualization and analytics, along with the ability to adapt to new technologies and drive continuous improvement in BI solutions. If you are enthusiastic about leveraging the power of data through Power BI, we encourage you to apply and join our dynamic team.

MinionLabs is looking for professionals with 1 - 4 Years of Experienced as Data Scientists professionals to join their team and help them improve their Energy Monitoring product and create new applications. If you are looking for a leadership role in a fast-growing early-stage company, they want you! They are looking for an analytical, results-driven candidate looking to build their skills as Data Scientists and have a passion for creating a better world. As a Data Scientist, you’ll work closely with IoT and Development teams to build new features and improve existing features and processes.

Qualifications:

• Academic background in a field with a statistical, mathematical, or computer science focus.

• Programming experience in Python and OOP’s Concept

• Analytical and quantitative problem-solving

• Knowledge of the basics of math and probability

• Well versed in working on Linux environment

• Experience in scripting with SQL

• Knowledge of applied statistics

• Having knowledge and hands-on experience in:

o Classical Machine Learning –

▪ Verifying data quality or ensuring it via data cleaning

▪ Performing statistical analysis techniques to gather insights from the dataset and leverage these findings while taking business decisions

▪ Have hands-on on algorithms like Logistic and Linear Regression, Boosting,

Bagging, Decision Trees, Naïve Bayes, SVM, Random Forest Classifier, KNN

▪ Have hands-on forecasting algorithms like ARIMA, SARIMA, LSTM, FbProphet,

Exponential Smoothing, Holt Winter o Deep Learning –

▪ Strong understanding of the under-the-hood fundamentals of deep learning

(layer details, backpropagation, etc.)

▪ Experience with Tensorflow, PyTorch and other Deep Learning Frameworks ▪ Understanding and using various neural network architectures such as fully connected networks, RNNs, LSTM, Transformers

▪ Comfortable with cluster environments and understands the related computer systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks during training of neural networks

• Knowledge of data science frameworks and libraries: PyTorch, Pandas, NumPy, sci-kit-learn, Matplotlib & Selenium

•      Understanding of cloud technologies

•      Effective communication skills

•      Drive and ability to learn recent technologies.

Roles and Responsibilities:

·      Perform statistical analysis

•       Work hands-on and lead the development and implementation of predictive models, data mining algorithms, and statistical analysis techniques.

•      Fine-tuning test results

•      Stay up to date with emerging trends and technologies in the field of data science and apply them to improve our analytical capabilities.

•      Build reports/ dashboard using Power BI / Excel

•      Build optimization algorithms to improve efficiency

• 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

The person holding this position is responsible for leading the solution development and implementing advanced analytical approaches across a variety of industries in the supply chain domain.

At this position you act as an interface between the delivery team and the supply chain team, effectively understanding the client business and supply chain.

Candidates will be expected to lead projects across several areas such as

• Demand forecasting
• Inventory management
• Simulation & Mathematical optimization models.
• Procurement analytics
• Distribution/Logistics planning
• Network planning and optimization

Qualification and Experience

• 4+ years of analytics experience in supply chain – preferable industries hi-tech, consumer technology, CPG, automobile, retail or e-commerce supply chain.
• Master in Statistics/Economics or MBA or M. Sc./M. Tech with Operations Research/Industrial Engineering/Supply Chain
• Hands-on experience in delivery of projects using statistical modelling

Skills / Knowledge

• Hands on experience in statistical modelling software such as R/ Python and SQL.
• Experience in advanced analytics / Statistical techniques – Regression, Decision tress, Ensemble machine learning algorithms etc. will be considered as an added advantage.
• Highly proficient with Excel, PowerPoint and Word applications.
• APICS-CSCP or PMP certification will be added advantage
• Strong knowledge of supply chain management
• Working knowledge on the linear/nonlinear optimization
• Ability to structure problems through a data driven decision-making process.
• Excellent project management skills, including time and risk management and project structuring.
• Ability to identify and draw on leading-edge analytical tools and techniques to develop creative approaches and new insights to business issues through data analysis.
• Ability to liaison effectively with multiple stakeholders and functional disciplines.
• Experience in Optimization tools like Cplex, ILOG, GAMS will be an added advantage.