Description:

As a Data Scientist with Compliance background, you will combine compliance expertise with data analytics skills.
You will analyze a wide range of unstructured communications data to address problems for customers, focusing on regulatory compliance and risk mitigation.
This position allows you to work at the intersection of data science and financial compliance, developing both technical and domain-specific skills.
Your responsibilities will include generating insights and creating reports on compliance trends and potential risks for internal or customer-related datasets.
You will perform exploratory data analysis on communication data to identify potential compliance risks.
Assisting in data annotation and quality review for compliance-related datasets will be part of your role.
You will participate in client/prospect guidance for machine learning model and analytic fine-tuning processes.
Your work will be divided into 50% exploratory data analysis, data annotations, and compliance review; 30% data science experiments and model building; 10% interaction with stakeholders to understand compliance and modeling needs; and 10% reporting and documentation.

Requirements:

You must have demonstrated expertise in adherence to financial regulations and implementing LOD practices in L1, L2, and L3 risk management practices providing compliance through risk assessments.
Knowledge of the rules and regulations of the Securities Exchange Commission (SEC), Financial Industry Regulatory Authority (FINRA), and state securities regulatory agencies is required.
A solid understanding of statistics and data science principles, including hypothesis testing, regression, classification, and clustering, is necessary.
Excellent verbal and written communication skills are essential for this role.
You should be a self-motivated learner with a collaborative mindset.
The ability to manage time efficiently and handle multiple priorities is crucial.
A Bachelor's degree in Computer Science, Applied Math, Statistics, Business, Finance, or a related field is required.
You must have 2+ years of experience working with data and analytics, including academic experience.
Familiarity with Git, Linux/Unix, and IDEs is necessary.
Knowledge of financial industry regulations and compliance practices like LoD is required.
Experience and training in Bank’s L1, L2, and L3 risk assessment for Supervision or Surveillance or AML risks is essential.
Preferred qualifications include a Master's degree in a relevant field, familiarity with cloud computing platforms (AWS, GCS, Azure), and experience with automated supervision/surveillance/compliance tools.

The salary for this role ranges from £60,000 to £80,000 a year, representing Smarsh's good faith estimate of possible base compensation.
Any applicable bonus programs will be discussed during the recruiting process.
The salary will be set based on various factors, including internal equity, experience, education, location, specialty, and training.
Local cost of living assessments are conducted for each new hire at the time of offer.
Smarsh values lifelong learners with a passion for innovating with purpose, humility, and humor.
Collaboration is emphasized, and the company works closely with popular communications platforms and leading cloud infrastructure platforms.
Smarsh uses the latest in AI/ML technology to help customers break new ground at scale.
The organization values diversity and believes in providing opportunities for everyone to be their authentic self.
Smarsh has received Best Places to Work Awards from Comparably.com, reflecting its commitment to leadership, culture, and developing its people.