Plotly Dash Skills: Build apps using Plotly Dash.
Company: S&P Global
Title: Sr Data Scientist
Category: Full time
Location: Mumbai, Maharashtra, India
Experience: Senior level
Application: Link to apply
About the job
S&P Global Market Intelligence
The Role: Senior Data Scientist
The Team
The Credit Analytics New Product Development team gathers intelligence from across the financial services market, including new technologies, and new approaches to alternative data sources, to help define how they have the potential to impact businesses within the sector. We then define product opportunities and build partnerships with internal teams and third parties to develop new products that deliver new innovations. We succeed through leveraging unique research, big data, and machine learning techniques, and quantifying non-traditional data sources and risk analysis in bespoke models that help businesses manage their approach. This team works toward implementing ideas at the junction of Risk, Fintech and Data Science.
The Impact
With the ever-expanding data sets and techniques to handle data, in this role you will use cutting edge techniques in domain languages to handle both traditional and alternative data sets and apply them into credit modelling.
We are innovating the way the essential intelligence is being collected and processed to support our clients’ decision making and risk monitoring needs. By leveraging the data science oriented technologies, we are delivering solutions faster and at scale, while maintaining the top notch quality standards.
What’s In It For You
We are a Fortune 500 company and recognized industry-leading provider of data and analytics: as such, we provide an unusually rich environment for data scientists to make an impact and grow personally and professionally. In addition to applying data science, you will have an opportunity to connect with leaders across S&P Global, our clients and partners; define new product opportunities; and be part of a lean, active, and professional team.
Join a dynamic team that solves diverse problems using, applied machine learning in finance with an end-to-end implementation of the solution: inception, prototyping, development, production, and GTM/selling/positioning. This is a high visibility role, and critical to the execution of our Analytics transformation strategy.
Responsibilities
- Leading the design, architecture, ML pipeline development for Universal Coverage.
- Design, execute and deploy projects aimed at solving high-impact business problems.
- Play a central role in all stages of the data science project life cycle, including:
- Identification of suitable data science project opportunities
- Partnering with business leaders, domain experts, and end-users to gain business understanding, data understanding, and collect requirements
- Evaluation/interpretation of results and presentation to business leaders
- Partnering with software developers to provide specifications for deploying models/algorithms into production systems, when applicable
- Perform exploratory data analysis, proof-of-concept modeling, and business cases necessary to generate partner consensus and internal support for your projects
- Dedicatedly communicate the vision and status of your data science projects, ensuring that accurate expectations are set and met across all levels of partners
- Present to customers projects and validate needs and requirements to feed into the business case
- Provide analysis and due diligence expertise with potential strategic partners
What We’re Looking For
- 5+ years’ experience in a quantitative, Data Science or other advanced data & predictive analytics role
- Practical experience with data mining, machine learning techniques, natural language processing, and data visualization - with an explicit aspiration to significantly enhance own skillset in those fields
- Experience of working on end-to-end data science pipelines: problem scoping, data gathering, exploratory data analysis, modelling, insights, visualizations, monitoring and maintenance
- Proven track record of strong analytical skills, learning agility, and independent thinking. Ability to make observations, form an option, and articulate to the team
- Typically requires a Graduate Degree in Math, Statistics, Engineering, Operational Research, or related field
- Strong English-speaking and writing skills required
- Hands on experience with implementing statistical models
- Experience in applying optimization and numerical methods
- Hands on experience with implementing Machine Learning techniques in a specific business application context.
Technical/Programming
- Expert Proficiency in Python or R
- Proficiency in, or willingness to learn, the other language – R or Python
- Applied Machine Learning models such as decision trees random forest, neural networks… whether in research or at work
- Experience in deploying apps in cloud native environment - Docker, Kubernetes, Sagemaker, AWS, Databricks, etc.
- Databases: SQL and any of SQL Server, Oracle, Snowflake, Postgres
- Shown success in using large amounts of data to solve analytical problems
- Experience with Natural Language Processing techniques, TensorFlow or PyTorch, SpaCy for entity recognition, ImageMagick, Tesseract, Table Detection techniques
- Built apps using Shiny/RStudio Connect and/or Plotly/Dash.
- Exposure to technologies such as Hadoop, Spark, no-SQL data stores such as Cassandra
- Familiarity with conventional software development languages - Scala, JavaScript, C#, Java, etc. - is a plus
- Ability to collaborate effectively with a diverse group of business, operational and technical partners
- Ability to communicate complex mathematical models and processes in straightforward, non-technical language
- Presentation skills: including presenting to senior management, stakeholders, and the executive team
Nice To Have
- Prior experience from the Economics/Financial industry
- Experience in building institutional/B2B financial models in the capital markets, risk management, or credit risk.