Bread Financial hires exciting Data Scientist job in Bangalore 2024.

Bread Financial is hiring for a Data Scientist job in Bangalore 2024. Both Freshers and Experienced candidates must apply for this position and Grab this opportunity.

Hello Data Folks, This is the great opportunity for all the individuals who have interest in Data Science domain, must start a job at Bread Financial for the position of Data Scientist job in Bangalore. If you are someone who is interested in this Job role must read there all responsibilities and requirements. And If you are someone who is looking for Data Science Jobs in Bengaluru or some other opportunities in Data Sector, must Subscribe to our Web Notification or follow us on other social media handles.

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About Company

Bread Financial is a company that offers a variety of financial solutions, including credit cards, loans, and savings accounts. They provide options like the Bread Cashback™ and Bread Rewards™ American Express® Credit Cards, which offer cash back and rewards on everyday purchases. Additionally, Bread Financial offers high-yield savings accounts with competitive interest rates and no monthly fees. For those looking to manage their purchases over time, Bread Pay™ allows customers to buy now and pay later through installment plans. Overall, Bread Financial aims to help customers shop, save, and manage their finances more effectively.

About Job Role

Data Science team delivers the best in class actionable business insights through cutting-edge predictive models and data science techniques. The Data Scientist is responsible for generating data-driven insights using advanced analytics and machine learning techniques to support enterprise data science needs within Bread Financial.

Responsibilities

Analytics – under supervision and guidance, completes the following:
1) extracts and samples data, conducts data integrity checks and applicable data pre-processing such as treatment of missing values and outliers.
2) conducts exploratory data analysis for preliminary data insights to drive the selection of modeling approach that best addresses the business problem.
3) reveals hidden data patterns by data mining using unsupervised learning techniques such as clustering analysis and factor analysis.
4) conducts feature engineering to create/derive model predictors with strong predictive power.

5) trains/tunes classification/regression models by applying supervised learning techniques such as generalized linear models assuming applicable underlying distributions such as logit and gamma, tree-based models such as decision trees, random forest, boosted trees, etc., and neural net models.
6) conducts proper model test/validation, diagnoses and fixes model issues (e.g., over-fitting) when applicable. Sizes the impact of using the models in production as part of the current strategy. Presents results and business case to manager. Provides support for implementation and monitoring of solutions that are implemented.

Collaboration – under supervision and guidance, translates analytical results into useful recommendations for review with manager. Demonstrates strong verbal and written communication skills when working with internal partners and when presenting results to various audiences. Develops foundational knowledge of credit card operations, banking, financial, loyalty rewards, retail, and credit card regulations while working with the business. Collaborates with other data scientists in the company to share best practices and data science innovations.

Data Science innovation – with direction from leader, researches industry trends in data science of new tools, emerging algorithms, advanced platforms, and alternative data to enhance modeling effectiveness and efficiency. Conducts use case testing for new tools/techniques/platforms/data and provides user input/feedback.

Model Risk Management – develops foundational knowledge on common model risks and related regulatory requirements; applies proper 1st line of defense controls during model development process to minimize model risk; creates comprehensive model governance documentation and archives model data, scripts, and results; collaborates with model risk management partners to complete model validation/auditing; completes remediation as required by model governance process.

Requirements

• Degree Required: Bachelor’s Degree
• Area of Study: Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science, or another quantitative field
• Years of Work Experience Required: Fresher or less than 1 year experience.
• Type / focus of work experience required: Must have done a course in Data science and Machine learning.

Knowledge, Skills and Abilities

Must:

• Data Science
• Machine Learning
• Structured Query Language (SQL)
• Python
• Strong Communication skills

Good to Have:

• Natural Language Processing (NLP)
• Cloud Experience (AZURE/AWS)

Why Join Bread Financial

• Professionals looking for an active and expanding environment will appreciate Bread Financial.
• The company encourages creative and progressive ideas especially in the recent development of data science and technology.
• At Bread Financial along with the award winning creative culture that value every employee respect, joy and support , the company is also focused and encouraged in the implementation of modern solutions which machine learning and predictive analytics are part of them.
• Within this framework, employees can work without having fears of backwardness in the respective industries.
• Bread Financial is a workplace with a culture that has been rewarded even, a culture where all their employees are appreciated and cared for.
• Work-life balance is highly encouraged at Bread Financial, along with the many other advantages concerning health, financial and personal wellness.
• Respective of the inclusive working culture, which celebrates individuality, all such contributions are acknowledged and rewarded.
• Being a technology-oriented financial service company, Bread Financial is also NAD, which means that there is also an opportunity for growth through payment, lending and saving businesses that are digitally oriented.
• The employees get to take part in specially designed high-stake projects that deal with financial technology and envision the technologies of the future, thus they get to influence the company in a productive way.
• Secondary, Bread Financial promotes career advancement in conventional and career paths along with unlimited opportunities for sharpening skills.
• Even with about 7000 associates worldwide, the work environment and culture at Bread Financial is team oriented and assists in the achievement of personal and professional satisfaction.
• To those in search of fulfilling work, the company’s undertakings towards responsibility in business and contribution to the society provides even more reasons to do so.

Career Growth and Opportunities

• At Bread Financial, the ambience is such that they expect all employees to develop both professionally and personally.
• Such a rich supportive environment brings about many innate as well as skilled capabilities of employees especially in the areas of data sciences, machine learning techniques and advanced analytics.
• Employees are also able to work on, and even, lead projects that aim at improving the business processes of the structure thanks to the agile business approach that the organization employs involving advanced tools such as predictive modeling.
• Most importantly, the Organization’s work culture promotes and empowers its employees to learn and improve themselves at all times without fear of falling behind.
• While on the job, people can take part in professional programs, workshops that improve their skills and get hands on in things like SQL, Python, and even Azure and AWS.
• Bread Financial also encourages employees to collaborate across the organization, allowing them to be involved in different areas of the business, including, but not limited to credit card, banking, and retail operations.
• In the case of employees who aspire for managerial positions, the organization, i.e. Bread Financial has additional managerial level structures that are designed to facilitate the movement of such employees to higher positions in the organizational hierarchy.
• The work environment of this organization is very gracious and all embrace employees fairly and encourage their career growth and development.
• Emphasizing the various ways in which training can be acquired and further development, Bread Financial is an ideal organization for individuals who wish to innovate and further their careers in an enabling, technology inclined atmosphere.

Industry Impact of the Role

• You will be critical in moving forward the financial industry as a Data Scientist within Bread Financial leveraging advanced analytics and machine learning for decision making insights.
• Here, you will be dealing with predictive models that enhance decisions in operational areas such as credit cards, banking, loyalty programs, and retail management.
• Data mining, unsupervised learning and feature engineering will be used to uncover the underlying patterns and trends which dictate certain business strategies.
• Your efforts do not limit you to individual projects.
• The knowledge you provide enables the Business and its partners to add value through the provision of innovations such as targeted payment solutions, enhanced loyalty rewards and credit card features.
• Your activities are normative in that they seek to improve operational efficiency, enhance client service experience as well as increase income for the Business Financial partners through the use of branding technology and the digital business strategy.
• Please note that you are encouraged to keep learning new data science skills as they emerge since they will enable you to help the company and even the entire financial services sector venture into new terrains.
• For this position, it is not just talk about hoping – it is about working in order to bring a change to service provision of present day financial solutions which will benefit the company and improve its competitive position and that of the financial ecosystem as a whole.

Learning and Development Opportunities

• Bread Financial places a significant value on its employees’ pursuit of knowledge and skills; hence, many such opportunities are provided.
• As a Data Scientist, you are provided with the materials and access to modern technologies, trends, and latest developments within the scope of data science and machine learning.
• In a bid to maintain the quality of employees, the management of Bread Financial encourages the subordinate workforce to conduct active research on the innovative advances in algorithms, platforms, and tools.
• This helps in maintaining the contemporary status of the company, both within the operations of the company and to the employees.
• Interactions with other personnel create a dependency and thus a capacity building structure, where such data scientists exchange helpful knowledge to each other so that you can widen your professional circle.
• In addition, factors such as Bread Financial also has a feline component in the way that it institutionalizes practice, enabling its employees to learn by adopting new tools and applications on real cases.
• Through this, they ensure that the employee’s ability of execution increases econometrically without reducing that of the firm.
• While technical skills and competencies are prioritized in most headhunting processes, Bread Financial wants to instill even soft skills in its employees.
• It seeks to enhance their growth through coaching, knowledge sharing, and exposing them to difficult business challenges.
• All those experiences make people successful and develop the economy of the company, and thus this is a great company for both professional and personal development.

Application Tips and Common Mistakes

• Before applying to the job post, make sure that your resume serves its purpose by showcasing relevant skills including Data Science, ML, Python, SQL is crucial.
• Make sure that you should customize your resume before applying particular job role and also add the relevant skills mentioned in Job description without any failure.
• Finally, always remember that your resume fulfills the expectations of the job description and also showcase your project work very well in your resume.

Rishikesh Deshmukh

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