Performance Marketing Manager

Review Criteria

• Strong Data Scientist/Machine Learnings/ AI Engineer Profile
• 2+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models
• Strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.
• Hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models
• Strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text
• Experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments
• Preferred (Company) – Must be from product companies

Job Specific Criteria

• CV Attachment is mandatory
• What's your current company?
• Which use cases you have hands on experience?
• Are you ok for Mumbai location (if candidate is from outside Mumbai)?
• Reason for change (if candidate has been in current company for less than 1 year)?
• Reason for hike (if greater than 25%)?

Role & Responsibilities

• Partner with Product to spot high-leverage ML opportunities tied to business metrics.
• Wrangle large structured and unstructured datasets; build reliable features and data contracts.
• Build and ship models to:
• Enhance customer experiences and personalization
• Boost revenue via pricing/discount optimization
• Power user-to-user discovery and ranking (matchmaking at scale)
• Detect and block fraud/risk in real time
• Score conversion/churn/acceptance propensity for targeted actions
• Collaborate with Engineering to productionize via APIs/CI/CD/Docker on AWS.
• Design and run A/B tests with guardrails.
• Build monitoring for model/data drift and business KPIs

Ideal Candidate

• 2–5 years of DS/ML experience in consumer internet / B2C products, with 7–8 models shipped to production end-to-end.
• Proven, hands-on success in at least two (preferably 3–4) of the following:
• Recommender systems (retrieval + ranking, NDCG/Recall, online lift; bandits a plus)
• Fraud/risk detection (severe class imbalance, PR-AUC)
• Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs, guardrails/simulation)
• Propensity models (payment/churn)
• Programming: strong Python and SQL; solid git, Docker, CI/CD.
• Cloud and data: experience with AWS or GCP; familiarity with warehouses/dashboards (Redshift/BigQuery, Looker/Tableau).
• ML breadth: recommender systems, NLP or user profiling, anomaly detection.
• Communication: clear storytelling with data; can align stakeholders and drive decisions.

Strong Implementation Specialist / Implementation Engineer / Technical Implementation Associate (Post-Sales SaaS) Profiles

Mandatory (Experience 1): Must have 1+ years of hands-on experience in software/tech Implementation roles within technical B2B SaaS companies, preferably working with global or US-based clients

Mandatory (Experience 2): Must have experience in executing and supporting end-to-end SaaS product implementations, including customer onboarding, workflow & configuration setup, data modeling/data setup, API-based integrations, and go-live support.

Mandatory (Experience 3): Must have strong technical fundamentals — ability to understand data models, debug API workflows, read JSON payloads, write basic SQL queries, and support configuration troubleshooting.

Mandatory (Experience 4): Must have basic hands-on experience writing scripts (preferably JavaScript) for data migration, configuration automation, or workflow customization in SaaS products.

Mandatory (Experience 5): Must have worked in post-sales environments, supporting customer success and delivery after deal closure, ensuring product adoption, accurate setup, and smooth go-live.

Mandatory (Experience 6): Must have experience collaborating cross-functionally with product, engineering, and sales teams to ensure timely resolution of implementation blockers and seamless client onboarding.

Mandatory (Company Type): B2B SaaS startup or growth-stage company

Strong performance marketer profile

Mandatory (Experience 1): Must have 2.5+ years of experience in performance marketing in B2C Fintech product companies

Mandatory (Tech Skills 1): Must have strong hands-on expertise in running campaigns on Google Ads, Meta Ads, LinkedIn Ads, Youtube, Whatsapp etc

Mandatory (Tech Skills 2): Must have 1+ experience in customer acquisition in FinTech, B2C

Mandatory (Tech Skills 3): Must have experience with Appsflyer, Branch, Mixpanel or similar analytical tools

Mandatory (Company): B2C Fintech Product companies (Targeted companies list given below)

Job Category: Software Development

Job Type: Full Time

Job Location: Bangalore

Gnani.ai aims to empower enterprises with AI based speech technology.

Gnani.ai is an AI-based Speech Recognition and NLP Startup that is working on voice-based solutions for large businesses. AI is the biggest innovation that is disrupting the market and we are at the heart of this disruption. Funded by one of the largest global conglomerates in the world, and backed a number of market leaders in the tech industry,

We are working with some of the largest companies in the banking, insurance, e-commerce and financial services sectors and we are not slowing down. With aggressive expansion plans, Gnani.ai aims to be the leader in the global market for voice-based solutions.

Gnani.ai is building the future for voice-based business solutions. If you are fascinated by AI and would like to work on the latest AI technologies in a high-intense, fast-growing and flexible work environment with immense growth opportunities, come and join us. We are looking for hard workers, who are ready to take on big challenges.

NLP Software Developer

Gnani.ai is looking to hire software developers with 0 to 2+ Years of experience, with a keen interest in designing and developing chat and voice bots. We are looking for an Engineer who can work with us in developing an NLP framework if you have the below skill set

Requirements :

• Proficient knowledge of Python
• Proficient understanding of code versioning tools, such as Git / SVN.
• Good knowledge of algorithms to find and implement tools for NLP tasks
• Knowledge of NLP libraries and frameworks
• Understanding of text representation techniques, algorithms, statistics
• Syntactic & Semantic Parsing
• Knowledge/work experience on No-SQL database Mongo.
• Good knowledge of Docker container technologies.
• Strong communication skills

Responsibilities :

• Develop NLP systems according to requirements
• Maintain NLP libraries and frameworks
• Design and develop natural language processing systems
• Define appropriate datasets for language learning
• Use effective text representations to transform natural language into useful features
• Train the developed model and run evaluation experiments
• Find and implement the right algorithms and tools for NLP tasks
• Perform statistical analysis of results and refine models
• Constantly keep up to date with the field of machine learning
• Implement changes as needed and analyze bugs

Good To Have :

Start up experience is a plus

• Understand the requirement and convert that into API design.
• Write the code independently 
• Unit testing and bug fixing
• Write code with standards and conventions and follow best practices.
• Know how to engineer a full-fledged system and not just write code to make things work.
• Knowledge of agile methodologies, scrum.
• Should be able to guide juniors.
• Communication with clients for requirement understanding.
• Code Merging and deployment

• REST APIs in Spring Boot and Spring Framework
• MySQL Database, complex SQL queries (like joining multiple tables)
• Spring Security, JWT Tokens
• Third party Integration
• Unix basic commands
• Apache Tomcat, Deployment of War in Unix environment.
• Jira or any other Issue/Task tracking systems.

We are looking for an outstanding Big Data Engineer with experience setting up and maintaining Data Warehouse and Data Lakes for an Organization. This role would closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Roles and Responsibilities:

• Develop and maintain scalable data pipelines and build out new integrations and processes required for optimal extraction, transformation, and loading of data from a wide variety of data sources using 'Big Data' technologies.
• Develop programs in Scala and Python as part of data cleaning and processing.
• Assemble large, complex data sets that meet functional / non-functional business requirements and fostering data-driven decision making across the organization.  
• Responsible to design and develop distributed, high volume, high velocity multi-threaded event processing systems.
• Implement processes and systems to validate data, monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes that depend on it.
• Perform root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
• Provide high operational excellence guaranteeing high availability and platform stability.
• Closely collaborate with the Data Science team and assist the team build and deploy machine learning and deep learning models on big data analytics platforms.

Skills:

• Experience with Big Data pipeline, Big Data analytics, Data warehousing.
• Experience with SQL/No-SQL, schema design and dimensional data modeling.
• Strong understanding of Hadoop Architecture, HDFS ecosystem and eexperience with Big Data technology stack such as HBase, Hadoop, Hive, MapReduce.
• Experience in designing systems that process structured as well as unstructured data at large scale.
• Experience in AWS/Spark/Java/Scala/Python development.
• Should have Strong skills in PySpark (Python & SPARK). Ability to create, manage and manipulate Spark Dataframes. Expertise in Spark query tuning and performance optimization.
• Experience in developing efficient software code/frameworks for multiple use cases leveraging Python and big data technologies.
• Prior exposure to streaming data sources such as Kafka.
• Should have knowledge on Shell Scripting and Python scripting.
• High proficiency in database skills (e.g., Complex SQL), for data preparation, cleaning, and data wrangling/munging, with the ability to write advanced queries and create stored procedures.
• Experience with NoSQL databases such as Cassandra / MongoDB.
• Solid experience in all phases of Software Development Lifecycle - plan, design, develop, test, release, maintain and support, decommission.
• Experience with DevOps tools (GitHub, Travis CI, and JIRA) and methodologies (Lean, Agile, Scrum, Test Driven Development).
• Experience building and deploying applications on on-premise and cloud-based infrastructure.
• Having a good understanding of machine learning landscape and concepts. 

Qualifications and Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Big Data Engineer or a similar role for 3-5 years.

Certifications:

Good to have at least one of the Certifications listed here:

    AZ 900 - Azure Fundamentals

    DP 200, DP 201, DP 203, AZ 204 - Data Engineering

    AZ 400 - Devops Certification