About this role:
Wells Fargo is seeking a Data Science Consultant.
In this role, you will:
- Participate in low to moderately complex initiatives by utilizing data-driven, advanced analytical and statistical techniques to identify trends, diagnose problems, and build actionable insights or recommendations
- Review and analyze business, operational, technical assignments, or challenges that require research, evaluation, and selection of alternatives to convert data into meaningful insights and recommendations
- Exercise independent judgment to guide medium risk business hypothesis generation
- Present recommendations and insights for resolving low to moderately complex business needs and problems; exercise independent judgment while developing an expertise in analytic capabilities
- Collaborate and consult with functional colleagues, internal partners, and stakeholders to drive recommendations and strategies based on data-driven analytical insights, trends, and patterns
- Conduct low to moderately complex predictive analytics to build actionable insights and recommendations
- Design and apply algorithms to mine large sets of structured and unstructured data from various sources
- Ensure data completeness, accuracy, and uniformity through cleaning and validation
- Interpret and analyze data, using advanced analytics modeling methods and programming, to isolate patterns that lead to recommendations to solve problems and influence business decisions and strategies
Want more jobs like this?
Get jobs in Hyderabad, India delivered to your inbox every week.
- 2+ years of data science experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
- 5+ years of experience in design, development, deployment and management of Machine Learning and NLP models for various use cases
- Data Analytics expertise in Analyzing structured and unstructured data for advanced analytics solutions
- Data preparation (complex datasets), exploratory data analysis to assess the fitment of the data for the appropriate machine learning models
- Leveraging statistical modeling for the betterment of analytical solutions
- Building explainable AI ML & NLP models using supervised, unsupervised, and deep learning algorithms
- Python libraries, SAS, SQL, and big data technologies such as Hadoop, Spark, Hive or AWS services
- Tools such as Scikit-learn, TensorFlow, PyTorch, NumPy/SciPy, Pandas.
- Knowledge of visualization frameworks using Power BI and Tableau
- Investment Banking / Capital Markets / Traded products and asset classes
- Minimal requirement - Banking and Financial Services
- Excellent verbal, written, and interpersonal skills
- Educational Qualification: MBA/PhD/M-Tech from premier universities
- Conceptualize, test and develop descriptive and predictive models using statistics / AI ML & NLP technologies.
- Create and perform end-to-end analysis, including designing research methods, data extraction, processing, analysis, visualization, presentation of results to stakeholders.
- Designs and implements robust, production-level microservices & APIs to expose algorithms and models.
- Innovate and design automation tools to drive internal processes and improve data quality.
- Experience in design, development, deployment and management of Machine Learning and NLP models for various use cases
- Data Analytics expertise in:
- Analyzing structured and unstructured data for advanced analytics solutions
*Job posting may come down early due to volume of applicants.
We Value Diversity
At Wells Fargo, we believe in diversity, equity and inclusion in the workplace; accordingly, we welcome applications for employment from all qualified candidates, regardless of race, color, gender, national origin, religion, age, sexual orientation, gender identity, gender expression, genetic information, individuals with disabilities, pregnancy, marital status, status as a protected veteran or any other status protected by applicable law.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
Candidates applying to job openings posted in US: All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
Applicants with Disabilities
To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .
Drug and Alcohol Policy
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
Wells Fargo Recruitment and Hiring Requirements:
a. Third-Party recordings are prohibited unless authorized by Wells Fargo.
b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.