Sales Director

Exp- 3-10 years

Notice period- Serving notice period or immediete

Location-Bangalore

Required Skills and Qualifications 

Backend: 

• Strong programming skills in Core Java, Java 8+ 

• Experience with Spring Boot, RESTful APIs, Microservices architecture 

• Good understanding of JPA/Hibernate, and SQL/NoSQL databases 

Frontend: 

• Proficient in React.js, JavaScript (ES6+), HTML5, CSS3 

• Experience with Redux, React Hooks, and component-based architecture 

• Familiarity with front-end build tools (Webpack, Babel, NPM)

Key Responsibilities

• Develop and maintain scalable backend services using Core Java / Spring Boot 

• Design and implement responsive, high-quality front-end interfaces using React.js 

• Integrate backend APIs with frontend components seamlessly 

• Collaborate with product managers, architects, and QA to deliver quality software 

• Ensure code quality through unit testing, code reviews, and performance tuning 

• Troubleshoot and debug production issues as needed 

What you’ll do?

Partnering with internal business owners (product, marketing, edit, etc.) to understand needs anddevelop custom analysis to optimize for user engagement and retention.

Good understanding of the underlying business and workings of cross functional teams for successful execution.

Design and develop analyses based on business requirement needs and challenges.

Leveraging statistical analysis on consumer research and data mining projects, including segmentation, clustering, factor analysis, multivariate regression, predictive modeling, etc.

Providing statistical analysis on custom research projects and consult on A/B testing and otherstatistical analysis as needed.

Other reports and custom analysis as required.

Identify and use appropriate investigative and analytical technologies to interpret and verify results.

Apply and learn a wide variety of tools and languages to achieve results.

Use best practices to develop statistical and/ or machine learning techniques to build models thataddress business needs.

Collaborate with the team in order to improve the effectiveness of business decisions throughthe use of data and machine learning/predictive modeling.

Innovate on projects by using new modeling techniques or tools.

Utilize effective project planning techniques to break down complex projects into tasks and ensure deadlines are kept. C

ommunicate findings to team and leadership to ensure models are well understood and incorporated into business processes.

Who you need to be?

Typically has 2 - 6 years of relevant experience.

Preferred education: Bachelor's degree in a technical field or equivalent experience Experience in advanced analytics, model building, statistical modeling, optimization, and machinelearning algorithms.

Machine Learning Algorithms: Crystal clear understanding, coding, implementation, error analysis, model tuning knowledge on Linear Regression, Logistic Regression, SVM, shallow Neural Networks, clustering, Decision Trees, Random forest, XGBoost, Recommender Systems, ARIMA and Anomaly Detection.

Feature selection, hyper parameters tuning, model selection and error analysis, boosting and ensemble methods.

Strong with programming languages like Python and data processing using SQL or equivalent andability to experiment with newer open-source tools.

Experience in normalizing data to ensure it is homogeneous and consistently formatted to enablesorting, query and analysis.

Experience designing, developing, implementing and maintaining a database and programs tomanage data analysis efforts.

Experience with big data and cloud computing viz. Spark, Hadoop (MapReduce, PIG, HIVE)

Experience in risk and credit score domains preferred.

Job location  Chennai/Bangalore (work from office-Hybrid)

Experience: 6+ years building and operating production ML systems that drive commercial decisions at scale. 

Location: Remote 

To streamline and fast-track screening, please submit your details here (if you haven’t already): https://airtable.com/appbtkr4odapnb5I6/pag05ROZwgz5AaLDG/form 

We’ll review your responses as part of the initial screening process. Please make sure you complete and submit all details through the form to be considered for the next stage. Submissions outside the form may not be considered.

Why This Role Matters

Terrabase builds decisioning infrastructure for enterprise customers: ranked recommendations, scoring pipelines, and policy-governed outputs that drive real commercial action. Our ML systems do not live in notebooks. They run multi-stage evaluation harnesses, apply structured governance rules, backtest against historical outcomes, and ship ranked outputs that customers act on daily.

This role owns the decisioning system end to end. That means the models, the eval harness, the policy layer, the production services, and the technical roadmap for where all of it goes next.

What You Will Do

Own the decisioning and ranking pipeline. Design, extend, and operate the end-to-end system: candidate generation in DuckDB, multi-stage scoring with LightGBM and AutoGluon, post-score policy application, and final ranked output delivery. You understand each layer well enough to debug latency, correctness, and coverage problems quickly, and to design the next version.

Lead the evaluation harness. Our eval pipeline runs multiple gates before any output ships: data health checks, specification validation, business rules enforcement, resolution checks, LLM-as-judge scoring, backtest against historical outcomes, and final output validation. You will own this harness, extend it as the system grows, and ensure every model or pipeline change is measurable and reproducible before it reaches a customer.

Apply policy logic with rigor. Our ML systems operate under structured governance rules that determine which offers apply to which customer segments, under what conditions. You will implement, test, and audit these rules in code, not configure them in a spreadsheet. Every exclusion must be traceable and explainable.

Engineer features that move metrics. Identify and build the behavioral signals, engagement indicators, contract features, and value-band attributes that improve model performance. Close the loop from feature hypothesis through offline evaluation to production monitoring. Own the data contracts between upstream sources and the scoring pipeline.

Build and maintain the production pipeline and service layer. The decisioning system is not a batch notebook. You will write and operate the Python pipeline and service layer that wraps model inference, handles edge cases, versions model artifacts, and connects to downstream consumers. You own CI, test coverage, reproducible training runs, monitoring, and production incidents.

Drive technical direction. Write design documents, lead code review, and set the engineering standard for the decisioning system. Help define the roadmap: what gets built, in what order, and why. Mentor contributors who work alongside you on this system.

Work forward-deployed. You will engage directly with customer stakeholders to understand business context, interpret model outputs, and translate commercial requirements into system constraints. You are accountable for customer delivery, not just model accuracy.

What We Are Looking For

• 6+ years building and operating production ML systems, not prototypes or research work
• Strong Python skills across the full ML lifecycle: data pipelines, feature engineering, model training, inference services, and monitoring
• Production experience with gradient boosting models (LightGBM, XGBoost)
• Hands-on with DuckDB or similar in-process analytical engines for large-scale data processing
• Evaluation discipline: held-out metrics, backtesting against historical data, multi-gate eval pipelines, LLM-as-judge patterns
• Experience applying business rules, policy overrides, or constraint layers on top of model outputs
• Engineering fundamentals: CI pipelines, data contracts, versioned artifacts, test coverage, incident response
• Technical leadership: design docs, code review, roadmap input, mentoring
• Comfort with forward-deployed work: you can run a meeting with a non-technical stakeholder and turn the output into a system requirement
• Comfort inheriting an existing production codebase, improving its structure, and raising reliability without rewriting everything from scratch

Bonus Points

• Experience with next-best-offer engines, customer-level targeting, or recommendation systems at scale
• Experience with AutoML frameworks (AutoGluon or similar) in a production scoring pipeline
• Thompson sampling, multi-armed bandits, or portfolio-level optimization experience
• Exposure to structured data from telecoms, financial services, or retail sectors
• Prior work owning a decisioning or ranking system as the technical lead

Life at Terrabase

We are a sharp, focused, fully remote team that ships to real enterprise customers weekly. You will own a system that drives measurable commercial outcomes, with high autonomy, generous cloud budgets, and a culture that prizes rigor over hype.

Terrabase is an equal-opportunity employer. We celebrate diversity and are committed to building an inclusive environment for every team member.

• On-Premise Infrastructure Management: Utilize 10-20 years of experience to oversee and optimize on-premise infrastructure, ensuring stability, scalability, and security.
• Cloud Infrastructure Management: Lead the implementation and management of AWS and Azure cloud environments, leveraging best practices and ensuring adherence to security standards. Must be cloud certified and proficient in managing PaaS services.
• Dynatrace Monitoring: Utilize Dynatrace expertise to implement and maintain effective monitoring solutions, ensuring proactive identification and resolution of performance issues.
• Technical Expertise: Demonstrate proficiency in a variety of technologies including Oracle, SQL Server, Shareplex for Oracle replication, Commvault, Windows, Linux, Solaris, SNMP Polling and Traps, Unix Extension, and more.
• Analytical Skills: Conduct complex analysis to optimize bulk metrics and alert profiles, ensuring efficient resource utilization and timely response to critical incidents.
• Cloud Integration: Facilitate inter-AWS account integration using Terraform IAM roles and integrate with other products such as Splunk, APIM, and VMWare to enhance overall infrastructure capabilities.
• Experience working with On-Premise Infrastructure
• Experience with AWS & Azure and Cloud Certified.
• Dynatrace Experience & Professional Certification

North American payroll,

As a presales manager, you will work closely across various verticals such as product development, engineering, sales and marketing, and project teams/customer relations to understand internal product and service capabilities. Build marketing and sales collaterals showcasing the company’s offerings and capabilities

Role will also include understanding the customer’s needs and building suitable solutions, working closely with engineering, delivery, and sales teams.  You will also be required to actively understand customer preferences and predict future needs for product development.

Key Responsibilities:

• Engagement with the customers and understanding of their needs and putting together solutions (products and services) that are aligned with the customers’ demands. 
• Responsible for supporting the business development team in putting together compelling proposals in response to RFPs.
• Responsible for bringing in industry/vertical specific expertise into building the solution and validating technical solutions from the service delivery team.
• Coordinating with 3rd party service providers and integrating their solution components into the overall proposals.
• Plan sales strategies in response to market and competitors’

actions.

• Work in sync with the product development team and develop

sustainable and commercially viable products.

• Understand customer needs and make sales presentations.
• Liaise with the marketing team to undertake demand-generating

activities such as trade shows, exhibitions or customer workshops.

• Prepare sales proposals and train sales representatives/executives

from time to time.

• Preparation of presentations about the products or services with their value proposition articulated for the usage of the sales team.
• Creation of marketing concepts and responding to customers’ RFPs and RFI’s for our local and global sales teams.
• Use domain expertise to articulate customer requirements appropriately to product and development teams
• Prepare and deliver solution-based product presentations and

demonstrations to customers.

• Execute on customer proof of concepts (POCs).
• Strong interpersonal skills, including the ability to present to an audience from C-Level to End User, clearly articulate the value Profile products will bring to an organization, gain trusted advisor respect, and help influence, make well-executed systems presentations and clearly articulate the product’s value.