Career

Job Code: DAUSRL2

Job Location: Remote, USA

Overview:

The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users.

Responsibilities:

Understand the day-to-day issues that our business faces, which can be better understood with data
Compile and analyze data related to business issues
Develop clear visualizations to convey complicated data in a straightforward fashion
We are looking for a curious and collaborative Analyst to solve business problems using data
As a Data Analyst, you will use analytical, statistical and programming skills to collect, analyze and interpret large datasets
You are expected to have strong data analytical skills with statistical background and hands-on experience in not only building machine learning models but also deploying them to production

Requirements:

Experience in solving business problems using various analytical and statistical techniques
You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data and communicate the findings using visualizations
You have experience writing SQL queries to create datasets for analytics and modeling (e.g. SQL, BigQuery, Hive)
Apply statistical analysis and visualization techniques to various data, Generate hypotheses about the underlying mechanics of the business process
Test hypotheses using various quantitative methods
Display drive and curiosity to understand the business process to its core
Network with domain experts to better understand the business mechanics that generated the data
Apply various ML and advanced analytics techniques to perform classification or prediction tasks
Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing
Testing of ML models, such as cross-validation, A/B testing, bias, and fairness
You have proven experience with at least one programming language (e.g. Python, Java, R) and are comfortable developing code in a team environment (e.g. git, notebooks)
Experience in statistical modeling and techniques like GLM, Random Forest, GBM, Neural Networks
You are self-motivated and curious with demonstrated creative and critical thinking capabilities
You have excellent verbal and written communication skills and experience in influencing decisions with information
Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering

Qualifications:

Bachelor’s degree or equivalent applied experience.
Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering
2+ years experience in solving business problems using analytical and statistical techniques
Experience in Fintech and/or Insurance industry will be a preferred

Apply →

Job Code: DEUSRL5

Job Location: Remote, USA

Overview:

The ideal candidate will play a pivotal role in building and operationalizing the minimally inclusive data necessary for the enterprise data and analytics initiatives following industry standard practices and tools. The bulk of the candidate’s work would be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for key data and analytics consumers like business/data analysts, data scientists or any persona that needs curated data for data and analytics use cases across the enterprise.

Responsibilities:

Managed data pipelines consist of a series of stages through which data flows. These data pipelines must be created, maintained and optimized as workloads move from development to production for specific use cases.
Drive Automation through effective metadata management. Using innovative and modern tools, techniques and architectures automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
Assist with renovating the data management infrastructure to drive automation in data integration and management, including
learning and using modern data preparation, integration and AI-enabled metadata management tools and techniques, tracking data consumption patterns, performing intelligent sampling and caching and monitoring schema changes
Work in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
Train counterparts such as [data scientists, data analysts, LOB users or any data consumers] in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
Collaborate with data governance teams to ensure that the data users and consumers use the data provisioned to them responsibly through data governance and compliance initiatives.
Travel to customer sites to deploy solutions and deliver workshops to educate and empower customers

Requirements:

Strong experience with various Data Management architectures like Data Warehouse, Data Lake, Data Hub and the supporting processes like Data Integration, Governance, Metadata Management
Strong ability to design, build and manage data pipelines for data structures encompassing data transformation, data models, schemas, metadata and workload management.
Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies. These should include ETL/ELT, data replication/CDC, message-oriented data movement, API design and access and upcoming data ingestion and integration technologies such as stream data integration, CEP and data virtualization.
Experience in working with data governance/data quality and data security teams and specifically information stewards and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification. Ability to build quick prototypes and to translate prototypes into data products and services in a diverse ecosystem.
Demonstrated success in working with large, heterogeneous datasets to extract business value using popular data preparation tools such as Trifacta, Paxata, Unifi, others to reduce or even automate parts of the tedious data preparation tasks.
Hands-On experience with BigQuery, Looker, Pub/Sub, Dataflow, Cloud Data Fusion, Cloud Storage, Cloud Composer, and Data Catalog or equivalent AWS products.BigQuery, Looker, Pub/Sub, Dataflow, Cloud Data Fusion, Cloud Storage, Cloud Composer, and Data Catalog
Strong experience with popular database programming languages including SQL, PL/SQL, others for relational databases and certifications on upcoming NoSQL/Hadoop oriented databases like MongoDB, Cassandra, others for non relational databases.
Strong experience in working with SQL on Hadoop tools and technologies including HIVE, Impala, Presto, and others from an open source perspective and Hortonworks Data Flow (HDF), Dremio, Informatica, Talend, and others from a commercial vendor perspective.
Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as R, Python, Java, C++, Scala, and others.
Strong experience in working with both open-source and commercial message queuing technologies such as Kafka, JMS, Azure Service Bus, Amazon Simple queuing Service, and others, stream data integration technologies such as Apache Nifi, Apache Beam, Apache Kafka Streams, Amazon Kinesis, and stream analytics technologies such as Apache Kafka KSQL Apache Spark Streaming Apache Samza, others.
Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities using tools like Git, Jenkins, Puppet, Ansible.
Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms
Demonstrated success in working with both IT and business while integrating analytics and data science output into business processes and workflows.
Basic experience working with popular data discovery, analytics and BI software tools like Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery.
Demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service and others
Adept in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse and automation of data flows between data managers and consumers across an organization

Qualifications:

5+ years of work experience in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks.
3+ years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative.
A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field or equivalent work experience is required.
Experience in Fintech and/or Insurance industry will be a preferred

Apply →

Job Code: DSUSRL3

Job Location: Remote, USA

Overview:

The data scientist is responsible for modeling complex business problems and discovering business insights through the use of statistical, algorithmic, mining, and visualization techniques. The data scientist contributes to building and developing the organization’s data infrastructure and supports the senior leadership with insights, management reports, and analysis for decision-making processes.

Responsibilities:

Understands the decision-making process, workflows, and business and information needs of business unit heads and service manager/owners.
Translates business needs into analytics/reporting requirements to support executive decisions and workflows with required information.
Proactively mines data warehouses to identify trends and patterns and generates insights for business units and senior leadership.
Performs large-scale experimentation to identify hidden relationships between variables in large datasets.
Researches and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient.
Determines requirements that will be used to train and evolve deep learning models and algorithms.
Visualizes information and develops engaging reports on the results of data analysis using data visualization tools.
Advises product teams on new products, features or updates through data-based recommendations.
Develops frameworks and processes to analyze unstructured information collected through social media platforms i.e., wikis, blogs, instant messaging, etc. and traditional sources such as e-mail and SharePoint.
Supports user experience specialists and information architects to enhance information visualization through development of dashboards and user interfaces.
Distributes best practices to analytics and product teams and provides consultations for their data-based experimentations.

Requirements:

Up-to-date knowledge of machine learning and data analytics tools and techniques - GLM, Random Forest, GBM, Neural Networks, Time Series.
Random Forest, GBM, Neural Networks, Time SeriesIntegrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing.
Strong knowledge in predictive modeling methodology.
Experienced at leveraging both structured and unstructured data sources.
Willingness and ability to learn new technologies on the job.
Demonstrated ability to communicate complex results to technical and non-technical audiences.
Demonstrated ability to work with minimal supervision.
Experience using statistics and machine learning to solve complex business problems.
Experience conducting statistical analysis with advanced statistical software, scripting languages, and packages - H2O, Tensorflow, Python, SQL.
Experience with big data analysis tools and techniques - Big Query, Hive, Spark, SQL Server.
Testing of ML models, such as cross-validation, A/B testing, bias and fairness.
Experience building and deploying predictive models, web scraping, and scalable data pipelines.

Qualifications:

Master’s degree or PhD in computer science, statistics, or related fields
3+ years experience as a Data Scientist
Experience in Fintech and/or Insurance industry will be a preferred

Apply →

Job Code: QAINRL1

Job Location: Remote, India

Overview:

The ideal candidate will be responsible for high-quality software delivery by planning, implementing, and automating quality assurance testing for the company. The software QA engineer ensures Responsibilities include developing test plans, creating test cases, writing test automation code, and reporting results.

Responsibilities:

Plan and implement testing (e.g., regression, functional, data validation, system integration, load, or performance tests) for new and existing functionality.
Work closely with development teams to design testing strategies and integrate testing into the development process.
Plan, create, execute, and automate test cases, working with business partners, developers, and other stakeholders.
Document and analyze test results and recommend corrective action.
Isolate, reproduce, manage, and maintain defects and test case databases, and verify fixes.
Support user acceptance testing conducted by business partners or end users.
Conduct exploratory testing and risk analysis for complex features, e.g., those that span across platforms or teams.
Identify opportunities to reduce testing time and effort by automating repeatable tests.
Enhance and maintain the test automation framework.
Understand and apply automated testing approaches such as model-based testing or record-and-replay.
Research, recommend, and implement new testing technologies and practices, such as incorporating machine learning.
Define and champion quality and testing best practices among development teams.
Collaborate and share information with other software QA engineers, e.g., by participating in a community of practice.
Provide guidance on setting up the pipeline for test cases including all necessary test scenarios, write test cases, execute, log defects when necessary, create test documents such as Test Summary Report
Review developers’ test plans to ensure comprehensive coverage.

Requirements:

Software development experience. Proficiency in Python
Experience writing test automation scripts.
Experience with SQL
Experience with test management tools (e.g., TestRail, XRay, Qtest, Quality Center, TM4J, Ghost Inspector).
Experience with test automation frameworks (e.g., Selenium, Cucumber, Cypress, Puppeteer, Playwright, TestNg, AutoIT, Grid, Webdriver).
Experience with application performance monitoring and observability tools.
Attention to detail and ability to identify, isolate and document defects.
Strong knowledge of agile practices and experience with agile planning tools (e.g., Jira, Monday.com).
Effective verbal and written communication skills for both technical and non-technical audiences.
Collaboration skills and ability to work on a team.
Adaptability and willingness to learn.

Qualifications:

Bachelor’s degree or equivalent applied experience.
1+ years of quality assurance testing experience
Background in enterprise applications is preferred.

Apply →

Job Code: UXINRL3

Job Location: Remote, India

Overview:

The ideal candidate will be responsible for creating high-quality, seamless user experiences for users by optimizing the functional experience and creating a polished and distinctive branded experience for products and applications. The candidate will apply user-centered design principles and techniques, and partner with development teams to inform and improve solution design.

Responsibilities:

Collaborate with business and technology stakeholders to develop a shared understanding of business and user goals.
Manage processes for gathering user and stakeholder feedback on existing UX and design ideas to iterate on design.
Design short- and long-term UX vision and strategy for products and applications supported.
Develop a deep understanding and documentation of customer journeys, personas and segmentation.
Collect and analyze user behaviors and needs through qualitative and quantitative user research such as interviews, field studies, surveys, A/B testing, digital experience monitoring, and usability testing.
Design solutions to address critical user pain points and opportunities to increase efficiency.
Apply user-centered design processes that incorporate data (e.g., from real user monitoring (RUM) technologies), user insights, and continuous feedback.
Develop and communicate design ideas through prototypes, wireframes, user flows, and other design deliverables.
Ensure applications and products supported meet objectives for usability, adhere to relevant design and accessibility standards, comply with brand strategy and identity guidelines, and deliver positive experiences.
Translate user research insights into stories, and partner with development team members to prioritize and deliver them.
Use and coach others on UI/UX tools, techniques, and best practices.
Communicate UX strategy and designs to internal and external stakeholders to build consensus and convey the impact of design decisions on user, customer, and business outcomes.
Contribute to and promote adoption of design patterns, standards, and systems.
Lead a team or provide coaching and mentorship to junior UI/UX designers.
Act as the UX lead on one or more product teams.

Requirements:

Deep skills in one or more of the following design disciplines: interaction design, user interface design, information design, graphic design.
Ability to distill complex concepts into design concepts and requirements.
Experience with user research methods and techniques (e.g., usability testing, contextual inquiry, etc.) and conducting user acceptance testing.
Ability to collaborate effectively and influence decision making across multidisciplinary teams.
Adaptability and a willingness to learn new skills, technologies, and frameworks.
Strong stakeholder management and facilitation skills, both for internal and external stakeholders and senior leaders.
Proficiency in UX design tools (e.g., Figma, Adobe XD, InVision, etc.) specifically relating to mockups, wire-framing, and web design.
Demonstrated ability to communicate complex technical information to various stakeholders verbally and in writing.
Basic understanding of agile development methodologies.

Qualifications:

Bachelor’s degree in Business, Product Design or a major design discipline (or equivalent training or years of experience)
3+ f experience as a UI/UX designer.
knowledge of CSS3, HTML5 and JavaScript will be preferred.
Prototyping via software skills (Axure, Balsamiq, Framer) or code is a plus

Apply →

Job Code: DAINRL2

Job Location: Remote, India

Overview:

The ideal candidate will use their passion for big data and analytics to provide insights to the business covering a range of topics. They will be responsible for conducting both recurring and ad hoc analysis for business users.

Responsibilities:

Understand the day-to-day issues that our business faces, which can be better understood with data
Compile and analyze data related to business issues
Develop clear visualizations to convey complicated data in a straightforward fashion
We are looking for a curious and collaborative Analyst to solve business problems using data
As a Data Analyst, you will use analytical, statistical and programming skills to collect, analyze and interpret large datasets
You are expected to have strong data analytical skills with statistical background and hands-on experience in not only building machine learning models but also deploying them to production

Requirements:

Experience in solving business problems using various analytical and statistical techniques
You think about data in terms of statistical distributions and have a big enough analytics toolbox to know how to find patterns in data and communicate the findings using visualizations
You have experience writing SQL queries to create datasets for analytics and modeling (e.g. SQL, BigQuery, Hive)
Apply statistical analysis and visualization techniques to various data, Generate hypotheses about the underlying mechanics of the business process
Test hypotheses using various quantitative methods
Display drive and curiosity to understand the business process to its core
Network with domain experts to better understand the business mechanics that generated the data
Apply various ML and advanced analytics techniques to perform classification or prediction tasks
Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing
Testing of ML models, such as cross-validation, A/B testing, bias, and fairness
You have proven experience with at least one programming language (e.g. Python, Java, R) and are comfortable developing code in a team environment (e.g. git, notebooks)
Experience in statistical modeling and techniques like GLM, Random Forest, GBM, Neural Networks
You are self-motivated and curious with demonstrated creative and critical thinking capabilities
You have excellent verbal and written communication skills and experience in influencing decisions with information
Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering

Qualifications:

Bachelor’s degree or equivalent applied experience.
Your academic background is in a quantitative field such as Computer Science, Statistics, Engineering
2+ years experience in solving business problems using analytical and statistical techniques
Experience in Fintech and/or Insurance industry will be a preferred

Apply →

Work @ Hudson Data

Join our team to help shape the future of Machine Learning and Smart Applications

USA

India

Work @ Hudson Data

Join our team to help shape the future of Machine Learning and Smart Applications

USA

01/

Data Analyst (DAUSRL2)

02/

Data Engineer (DEUSRL5)

03/

Data Scientist (DSUSRL3)

India

01/

Frontend Engineer (FEINRL2)

02/

Backend Engineer (BEINRL2)

03/

Quality Assurance Engineer (QAINRL1)

04/

UX/UI Engineer (UXINRL3)

05/

Data Analyst (DAINRL2)