Graphic / Branding designer

Key Responsibilities:

Sales and Business Development:

• Lead the branch team to achieve sales targets for Loan Against Property (LAP) products, ensuring overall growth in the branch's portfolio.
• Develop and implement strategies to acquire new clients, cross-sell products, and maintain long-term relationships with customers.
• Monitor market trends and competitor activities to identify opportunities and stay ahead of market demands.
• Promote the LAP product offerings through various channels, including partnerships, referral networks, and local events.

Team Leadership and Management:

• Manage, mentor, and guide the sales and operational teams to achieve individual and branch-wide sales goals.
• Conduct regular performance reviews and provide coaching and training to enhance the sales team’s skills.
• Ensure adherence to organizational standards and processes in customer acquisition and relationship management.

Customer Relationship Management:

• Establish and maintain strong relationships with key clients, stakeholders, and other business partners.
• Provide high-level support for the LAP product offering, including assisting clients with queries and guiding them through the loan process.
• Resolve customer issues or concerns related to LAP applications and ensure timely and efficient processing.

Operational Management:

• Oversee the day-to-day operations of the branch, including loan origination, documentation, disbursement, collections, and compliance.
• Ensure the branch maintains a smooth, efficient, and compliant operation in line with internal policies and external regulations.
• Monitor and maintain branch financials, including revenue, expenses, and profitability.

Reporting and Compliance:

• Provide regular reports to senior management on branch performance, including sales achievements, operational issues, and market trends.
• Ensure all processes comply with regulatory guidelines, including KYC (Know Your Customer) and AML (Anti-Money Laundering) policies.

About Hudson Data

At Hudson Data, we view AI as both an art and a science. Our cross-functional teams — spanning business leaders, data scientists, and engineers — blend AI/ML and Big Data technologies to solve real-world business challenges. We harness predictive analytics to uncover new revenue opportunities, optimize operational efficiency, and enable data-driven transformation for our clients.

Beyond traditional AI/ML consulting, we actively collaborate with academic and industry partners to stay at the forefront of innovation. Alongside delivering projects for Fortune 500 clients, we also develop proprietary AI/ML products addressing diverse industry challenges.

Headquartered in New Delhi, India, with an office in New York, USA, Hudson Data operates globally, driving excellence in data science, analytics, and artificial intelligence.

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About the Role

We are seeking a Data Analyst & Modeling Specialist with a passion for leveraging AI, machine learning, and cloud analytics to improve business processes, enhance decision-making, and drive innovation. You’ll play a key role in transforming raw data into insights, building predictive models, and delivering data-driven strategies that have real business impact.

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Key Responsibilities

1.⁠ ⁠Data Collection & Management

• Gather and integrate data from multiple sources including databases, APIs, spreadsheets, and cloud warehouses.

• Design and maintain ETL pipelines ensuring data accuracy, scalability, and availability.

• Utilize any major cloud platform (Google Cloud, AWS, or Azure) for data storage, processing, and analytics workflows.

• Collaborate with engineering teams to define data governance, lineage, and security standards.

2.⁠ ⁠Data Cleaning & Preprocessing

• Clean, transform, and organize large datasets using Python (pandas, NumPy) and SQL.

• Handle missing data, duplicates, and outliers while ensuring consistency and quality.

• Automate data preparation using Linux scripting, Airflow, or cloud-native schedulers.

3.⁠ ⁠Data Analysis & Insights

• Perform exploratory data analysis (EDA) to identify key trends, correlations, and drivers.

• Apply statistical techniques such as regression, time-series analysis, and hypothesis testing.

• Use Excel (including pivot tables) and BI tools (Tableau, Power BI, Looker, or Google Data Studio) to develop insightful reports and dashboards.

• Present findings and recommendations to cross-functional stakeholders in a clear and actionable manner.

4.⁠ ⁠Predictive Modeling & Machine Learning

• Build and optimize predictive and classification models using scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, and H2O.ai.

• Perform feature engineering, model tuning, and cross-validation for performance optimization.

• Deploy and manage ML models using Vertex AI (GCP), AWS SageMaker, or Azure ML Studio.

• Continuously monitor, evaluate, and retrain models to ensure business relevance.

5.⁠ ⁠Reporting & Visualization

• Develop interactive dashboards and automated reports for performance tracking.

• Use pivot tables, KPIs, and data visualizations to simplify complex analytical findings.

• Communicate insights effectively through clear data storytelling.

6.⁠ ⁠Collaboration & Communication

• Partner with business, engineering, and product teams to define analytical goals and success metrics.

• Translate complex data and model results into actionable insights for decision-makers.

• Advocate for data-driven culture and support data literacy across teams.

7.⁠ ⁠Continuous Improvement & Innovation

• Stay current with emerging trends in AI, ML, data visualization, and cloud technologies.

• Identify opportunities for process optimization, automation, and innovation.

• Contribute to internal R&D and AI product development initiatives.

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Required Skills & Qualifications

Technical Skills

• Programming: Proficient in Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM, TensorFlow, Keras, H2O.ai).

• Databases & Querying: Advanced SQL skills; experience with BigQuery, Redshift, or Azure Synapse is a plus.

• Cloud Expertise: Hands-on experience with one or more major platforms — Google Cloud, AWS, or Azure.

• Visualization & Reporting: Skilled in Tableau, Power BI, Looker, or Excel (pivot tables, data modeling).

• Data Engineering: Familiarity with ETL tools (Airflow, dbt, or similar).

• Operating Systems: Strong proficiency with Linux/Unix for scripting and automation.

Soft Skills

• Strong analytical, problem-solving, and critical-thinking abilities.

• Excellent communication and presentation skills, including data storytelling.

• Curiosity and creativity in exploring and interpreting data.

• Collaborative mindset, capable of working in cross-functional and fast-paced environments.

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Education & Certifications

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

• Master’s degree in Data Analytics, Machine Learning, or Business Intelligence preferred.

• Relevant certifications are highly valued:

• Google Cloud Professional Data Engineer

• AWS Certified Data Analytics – Specialty

• Microsoft Certified: Azure Data Scientist Associate

• TensorFlow Developer Certificate

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Why Join Hudson Data

At Hudson Data, you’ll be part of a dynamic, innovative, and globally connected team that uses cutting-edge tools — from AI and ML frameworks to cloud-based analytics platforms — to solve meaningful problems. You’ll have the opportunity to grow, experiment, and make a tangible impact in a culture that values creativity, precision, and collaboration.

Data Delivery Manager is responsible for managing and overseeing the end-to-end delivery of data

solutions, from data architecture and ingestion to processing, analysis, and reporting. This role

ensures that data projects are completed on time, within scope, and aligned with business

objectives. The Data Delivery Manager works with cross-functional teams, including data

engineers, analysts, and other stakeholders, to deliver high-quality data solutions. Key

Responsibilities: Project and Program Management: o Lead and manage the delivery of data-

driven projects, ensuring they are completed on time and within budget. o Develop and maintain

project plans, timelines, and resource allocation. o Monitor project progress and proactively

identify risks, implementing solutions to ensure successful project completion. o Ensure alignment

between data initiatives and business goals, maintaining continuous communication with

stakeholders. Stakeholder Engagement: o Serve as the primary point of contact between business

stakeholders and the data team, translating business requirements into technical specifications. o

Collaborate with business leaders to understand data needs and develop solutions that meet

those needs. o Provide regular updates on project status, risks, and key deliverables to

stakeholders and leadership teams. o Facilitate meetings to gather requirements and

communicate project milestones. Data Strategy & Architecture: o Oversee the design and

implementation of data solutions that support business objectives. o Ensure adherence to data

governance and quality standards throughout the data pipeline lifecycle. o Collaborate with data

architects to define scalable, secure, and high-performance data architectures. o Support data

integration initiatives across different platforms, ensuring smooth and efficient data flow. Team

Leadership and Development: o Manage cross-functional teams of data engineers, analysts, and

other professionals to deliver projects effectively. o Provide leadership and mentoring to team

members, fostering a culture of collaboration, innovation, and continuous learning. o Set clear

expectations, performance goals, and career development opportunities for the team. o Address

and resolve any team challenges, ensuring high levels of productivity and motivation. Quality

Assurance: o Ensure the accuracy, reliability, and quality of data solutions by implementing robust

testing, validation, and review processes. o Develop and enforce data standards, best practices,

and methodologies to ensure consistent, high-quality deliverables. o Drive continuous

improvement initiatives, analyzing past projects and identifying areas for enhancement. Risk

Management and Troubleshooting: o Identify potential risks to project delivery, including data

pipeline issues, resource shortages, or technical blockers, and implement mitigation strategies. o

Troubleshoot and resolve data-related issues and challenges during the project lifecycle.

Reporting and Analytics: o Oversee the creation and maintenance of data dashboards, reports, and

performance metrics. o Ensure that data solutions provide actionable insights for the business,

driving informed decision-making. Experience: o 5+ years of experience in managing programs

related to data management, data engineering, or analytics. o Proven track record in managing

data projects and delivering data solutions in a timely manner. o Experience with data integration,

data warehousing, and data modeling. o Strong understanding of data pipeline management, ETL

processes, and data analytics. Skills: o In-depth knowledge of data management tools and

technologies (e.g., SQL, NoSQL, ETL tools, cloud platforms such as AWS, Google Cloud, or Azure).

o Proficient in project management methodologies (Agile, Scrum, Waterfall). o Strong leadership

and team management skills, with the ability to drive collaboration across different functions. o

Excellent communication skills with the ability to translate complex data-related concepts into

understandable terms for non-technical stakeholders. o Analytical mindset with strong problem-

solving abilities. o Knowledge of data visualization and reporting tools (e.g., Power BI, Tableau,

Looker) is a plus. Certifications: o Project Management Professional (PMP) or Scrum Master

certification (preferred). o Data-related certifications (e.g., AWS Certified Big Data, Google

Professional Data Engineer) are a plus. Preferred Skills: o Experience with big data technologies

(e.g., Hadoop, Spark, Kafka). o Familiarity with machine learning or AI applications related to data

solutions. o Experience with data governance and compliance (e.g., GDPR).

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Responsibilities: 

• Develop backend systems for our first product
• Build reliable, secure and performant backend systems
• Drive test coverage and continuous delivery automation within the team
• Mentor and provide feedback to teammates

Requirements:

• 5+ years of software development experience
• Strong computer science fundamentals
• Deep and wide knowledge of Java ecosystem
• Can write code that is readable, maintainable, secure and performant
• Know the importance of tests and how to approach writing different types of tests
• Good intuition for REST API design
• Deep understanding of relational databases, transactions, entity-relationship modeling
• Comfortable writing highly concurrent systems
• Experienced in using profilers, tuning garbage collection, optimizing SQL queries

Bonus:

• Understanding of domain-driven design concepts like ubiquitous language, bounded contexts, aggregates and domain events
• Know how to use test driven development as a design tool
• Good intuition for the principles underlying object-orientation, particularly encapsulation
• Understand the importance of immutability and of reducing the state-space of objects
• Know how to refactor large codebases safely
• Seek to identify key underlying ideas and use those as building blocks before reaching for shiny new tools

Role – Technical Architect

ZipLoan is looking out for a strong technology leader of Software Product Engineering, with a Technical Experience of about 12+ years, and hands-on experience in Software Product Development and ownership. You will head our Platform team which will be tasked with building ZipLoan's platform layer along with a set of engineers reporting to you.

Role:

1. Understand the business end-to-end in order to drive a use-case driven architecture.
2. Identify parts of the code-base which can be made reusable as modules or services.
3. Propose architecture improvements to provide reliability and robustness at scale.
4. Provide a roadmap for evolution of the technology ecosystem.
5. Identify and erase technical debt.
6. Provide consultancy to engineering teams on specific design challenges.
7. Propose engineering best practices and help teams in adopting them.

1. 12 years min experience in core software development.
2. Hands-on experience building consumer Web/mobile apps at scale.
3. Strong exposure to open-source technology – Python and other languages,

Linux, SQL and NoSQL databases, Web development frameworks

1. Strong architecture skills.
2. Ability to mentor engineering team members effectively.
3. Preferably a strong full-stack engineer or at least strong backend skills with some front-end skill.