JSR Tech Consulting
Long term, contract‑to‑hire position with a major financial firm.
Hybrid work environment: 3 days a week in the office in Newark, NJ.
As a Senior Data Scientist on the Data Science team, you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians, and Actuaries tasked with mining our industry‑leading internal data to develop new analytics capabilities for our businesses. The role requires a rare combination of sophisticated analytical expertise, business acumen, strategic mindset, client relationship skills, problem solving, and a passion for generating business impact.
Here is what you can expect in a typical day:
Hands‑on development of sophisticated data science solutions comprising the portfolio developed by the Director Data Scientist and the technical requirements specified by the Director Data Scientist.
Hands‑on data analysis, model development, model training, model testing, and model deployment.
Continuous research of new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques.
Write production‑level code and partner with machine learning engineers to push development code into production.
Partner with machine learning engineers to productionize machine learning models; partner with data engineers to build data pipelines; partner with software engineers to integrate solutions with business platforms.
Work closely with the business and data science lead to recommend and develop models for customer engagement and wellness use cases.
Manage external vendors in the execution of the data science development process.
Skills and Expertise
Advanced degree (M.S., Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial Science, Data Science, or comparable quantitative disciplines.
Experience working on complex problems where analysis of situations or data requires in‑depth evaluation of various factors.
Knowledge of business concepts, tools, and processes needed for sound decision‑making in the context of the company’s business.
Experience in research, designing experiments (e.g., A/B testing), working with claims and customer experience data. A behavior science background is preferred but not required.
Excellent problem‑solving, communication, and collaboration skills and the ability to continuously learn through self‑initiative.
Applied Experience With
Data Acquisition and Transformation: Acquiring data from disparate sources using APIs, SQL, and NoSQL; transforming data with SQL, NoSQL, and Python; visualizing data using Python and R.
Database Management: Understanding database structure, cloud/AWS environments, primary and foreign key relationships, table design, and database schemas.
Model Deployment: Knowledge of the Model Development Life Cycle, CI/CD/CT pipelines (e.g., Jenkins, CloudBees, Harness), A/B testing, MLFlow, AWS SageMaker pipelines, and model/data versioning.
Statistics and Computing: Proficiency in Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science fundamentals, Bayesian statistics, time‑series analysis, and experimentation techniques.
Data Wrangling: Preparing and mapping raw data for analysis; processing large datasets (structured and unstructured).
Machine Learning: Understanding of machine learning theory, mathematics underlying algorithms, building, training, testing, monitoring models, and NLP expertise.
Programming Languages: Proficiency in Python, R, SQL, Java or Scala, and Cypher.
Payrate: $55–$65 per hour.
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Hybrid work environment: 3 days a week in the office in Newark, NJ.
As a Senior Data Scientist on the Data Science team, you will partner with our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians, and Actuaries tasked with mining our industry‑leading internal data to develop new analytics capabilities for our businesses. The role requires a rare combination of sophisticated analytical expertise, business acumen, strategic mindset, client relationship skills, problem solving, and a passion for generating business impact.
Here is what you can expect in a typical day:
Hands‑on development of sophisticated data science solutions comprising the portfolio developed by the Director Data Scientist and the technical requirements specified by the Director Data Scientist.
Hands‑on data analysis, model development, model training, model testing, and model deployment.
Continuous research of new methods for problem solution, including new algorithms, modeling techniques, and data analytics techniques.
Write production‑level code and partner with machine learning engineers to push development code into production.
Partner with machine learning engineers to productionize machine learning models; partner with data engineers to build data pipelines; partner with software engineers to integrate solutions with business platforms.
Work closely with the business and data science lead to recommend and develop models for customer engagement and wellness use cases.
Manage external vendors in the execution of the data science development process.
Skills and Expertise
Advanced degree (M.S., Ph.D.) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial Science, Data Science, or comparable quantitative disciplines.
Experience working on complex problems where analysis of situations or data requires in‑depth evaluation of various factors.
Knowledge of business concepts, tools, and processes needed for sound decision‑making in the context of the company’s business.
Experience in research, designing experiments (e.g., A/B testing), working with claims and customer experience data. A behavior science background is preferred but not required.
Excellent problem‑solving, communication, and collaboration skills and the ability to continuously learn through self‑initiative.
Applied Experience With
Data Acquisition and Transformation: Acquiring data from disparate sources using APIs, SQL, and NoSQL; transforming data with SQL, NoSQL, and Python; visualizing data using Python and R.
Database Management: Understanding database structure, cloud/AWS environments, primary and foreign key relationships, table design, and database schemas.
Model Deployment: Knowledge of the Model Development Life Cycle, CI/CD/CT pipelines (e.g., Jenkins, CloudBees, Harness), A/B testing, MLFlow, AWS SageMaker pipelines, and model/data versioning.
Statistics and Computing: Proficiency in Calculus, Multivariable Calculus, Linear Algebra, Differential Equations, Probability, Statistics, Applied Probability, Applied Statistics, Computer Science fundamentals, Bayesian statistics, time‑series analysis, and experimentation techniques.
Data Wrangling: Preparing and mapping raw data for analysis; processing large datasets (structured and unstructured).
Machine Learning: Understanding of machine learning theory, mathematics underlying algorithms, building, training, testing, monitoring models, and NLP expertise.
Programming Languages: Proficiency in Python, R, SQL, Java or Scala, and Cypher.
Payrate: $55–$65 per hour.
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