Data Scientist with Compliance Expertise
Smarsh
As a Data Scientist with Compliance background at our company, you will play a crucial role in combining compliance expertise with data analytics skills. You'll analyze a wide range of unstructured communications data to address problems for our customers, focusing on regulatory compliance and risk mitigation. This position offers a unique opportunity to work at the intersection of data science and financial compliance, allowing you to develop both technical and domain-specific skills. What will you do?Generate insights and create reports on compliance trends and potential risks for internal or customer related datasetsPerform exploratory data analysis on communication data to identify potential compliance risksAssist in data annotation and quality review for compliance-related datasetsParticipate in client/prospect guidance for machine learning model and analytic fine-tuning processes50% Exploratory data analysis, data annotations, and compliance review30% Data science experiments and model building10% Interaction with stakeholders to understand compliance and modeling needs10% Reporting and documentation
What will you bring?Demonstrated expertise in adherence to financial regulations and implementing LOD practices in L1, L2 and L3 risk anagement 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 agenciesUnderstanding of statistics and data science principles (hypothesis testing, regression, classification, clustering, etc.)Excellent verbal and written communication skillsSelf-motivated learner with a collaborative mindsetAbility to manage time efficiently and handle multiple priorities
Required Education and ExperienceBachelor's degree in Computer Science, Applied Math, Statistics, Business, Finance, or a related field2+ years of experience working with data & analytics (including academic experience)Familiarity with Git, Linux/Unix, and IDEsKnowledge of financial industry regulations and compliance practices like LoDExperience and Training in Bank’s L1, L2 and L3 risk assessment for Supervision or Surveillance or AML risks.
Preferred QualificationsMaster's degree in a relevant fieldFamiliarity with cloud computing platforms (AWS, GCS, Azure)Experience with automated supervision/surveillance/compliance tools £60,000 - £80,000 a yearThe above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Any applicable bonus programs will be discussed during the recruiting process.
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training. Local cost of living assessments are done for each new hire at the time of offer.About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
What will you bring?Demonstrated expertise in adherence to financial regulations and implementing LOD practices in L1, L2 and L3 risk anagement 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 agenciesUnderstanding of statistics and data science principles (hypothesis testing, regression, classification, clustering, etc.)Excellent verbal and written communication skillsSelf-motivated learner with a collaborative mindsetAbility to manage time efficiently and handle multiple priorities
Required Education and ExperienceBachelor's degree in Computer Science, Applied Math, Statistics, Business, Finance, or a related field2+ years of experience working with data & analytics (including academic experience)Familiarity with Git, Linux/Unix, and IDEsKnowledge of financial industry regulations and compliance practices like LoDExperience and Training in Bank’s L1, L2 and L3 risk assessment for Supervision or Surveillance or AML risks.
Preferred QualificationsMaster's degree in a relevant fieldFamiliarity with cloud computing platforms (AWS, GCS, Azure)Experience with automated supervision/surveillance/compliance tools £60,000 - £80,000 a yearThe above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting.
Any applicable bonus programs will be discussed during the recruiting process.
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training. Local cost of living assessments are done for each new hire at the time of offer.About our culture
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world’s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
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