86 applicants

Company

Original Job Post

Mitsubishi HC Capital America, Inc. · 3 days ago

Data Scientist

Norwalk, CT

Full-time

Onsite

Senior Level

$217K/yr - $242K/yr

12+ years exp

Wonder how qualified you are to the job?

Maximize your interview chances

CommercialFinance

Insider Connection @Mitsubishi HC Capital America, Inc.

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Lead the design and development of enterprise-grade deep analytics.

Explore and analyze large, complex datasets to identify patterns, trends, and correlations.

Develop hypothesis-driven analyses to uncover actionable insights.

Design, develop, and deploy predictive models and machine learning algorithms to address business challenges.

Optimize model performance through feature engineering, parameter tuning, and validation techniques.

Communicate findings and recommendations to stakeholders through clear and compelling data visualizations, reports, and presentations.

Collaborate with teams across the organization to translate data-driven insights into actionable strategies.

Stay abreast of the latest advancements in data science, machine learning, and analytics technologies.

Implement automation and streamline processes to optimize the entire data and analytics platform, ensuring efficient throughput and high-performance outcomes.

Recognize, devise, and execute internal process enhancements, including automation of manual tasks, optimizing data delivery, and redesigning architecture or infrastructure to enhance scalability.

Collate large, intricate datasets that align with functional and non-functional business demands.

Develop processes that facilitate data transformation, manage data structures, metadata, dependencies, and workload management.

Collaborate with business users to understand functional and data requirements, contributing to the enhancement of data models and pipelines.

Apply analytical and problem-solving skills to diagnose and resolve intricate technical issues.

Create, maintain, and continuously enhance scalable data pipelines, while also developing new data source integrations to accommodate the growing volume and complexity of data.

Designing, implementing, and managing data extraction, transformation, and loading (ETL) processes.

Creating comprehensive technical specification documents and application interface designs.

Creating data processing and integration solutions for both batch and real-time scenarios, proficiently handling structured and unstructured data.

Participate in design discussions, code reviews, and project-related team meetings.

Ensuring data security and compliance with relevant regulations and best practices in all data operations.

Troubleshooting and resolving data and system issues, stepping in when necessary to address outages and challenges.

Other duties and responsibilities as assigned or needed.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Azure OpenAIAzure NotebooksPythonRSQLData ManipulationStatistical AnalysisMachine LearningSupervised LearningUnsupervised LearningData VisualizationPowerBITableauData IntegrationSelf-Service Data PreparationRequirements AnalysisPrototypingBig Data TechnologiesHadoopSparkDeep LearningNatural Language ProcessingReinforcement LearningMachine Learning Model DeploymentCognitive AbilityProblem-SolvingCommunicationCollaborationAnalytical Ability

Required

Must have experience developing and deploying Data Science solutions leveraging components like Azure OpenAI and Azure Notebooks.

Proven work experience, 12+ years in Data Science or deep analytics in the financial sector.

Proficiency in programming languages such as Python, R, or SQL with experience in data manipulation, statistical analysis, and machine learning.

Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.

Strong expertise in data visualization tools such as PowerBI or Tableau.

Excellent communication and collaboration skills, with the ability to distill complex technical concepts into understandable insights for non-technical stakeholders.

Strong problem-solving skills and a passion for driving business impact through data-driven decision-making.

Experience working with data integration techniques & self-service data preparation.

Experience in requirements analysis, design, and prototyping.

Experience with big data technologies such as Hadoop and Spark.

Strong knowledge or advanced analytics techniques such as deep learning, natural language processing, or reinforcement learning.

Experience deploying machine learning models into production.

Thinking Skills – Cognitive Ability, Analytical Ability, Problem-Solving

Technical / Professional – Detail Oriented, Thoroughness