Product manager (B2B SaaS),

Job Title: Marketing Executive

Job Overview:

We are looking for an experienced, proactive, and self-driven Marketing Executive who can independently manage and execute the overall marketing function. This role requires a strong understanding of both traditional and digital marketing, combined with the ability to

plan, implement, and monitor marketing activities end-to-end.

The ideal candidate will take full ownership of marketing initiatives, coordinate with internal teams, and drive brand visibility, lead generation, and marketing performance with minimal

supervision.

Key Responsibilities:

1. Marketing Strategy & Execution (Core Responsibility)

• Develop and execute quarterly and annual marketing plans.

• Plan and implement campaigns for product promotion, lead generation, and brand building.

• Ensure consistent branding and messaging across all channels.

• Collaborate with sales, product, and leadership teams to align marketing initiatives

with business goals.

2. Digital Marketing (Part of the Role)

PPC & Lead Generation

• Plan, manage, and optimise Google Ads and other paid campaigns.

• Track performance metrics (CTR, CPC, CPA, conversions, ROI) and refine campaigns.

• Develop effective ad copies and assist with landing page enhancements.

SEO & Website Management

• Implement on-page/off-page SEO strategies to improve organic search visibility.

• Conduct keyword research, optimise content, and review analytics.

• Coordinate with design/content teams to ensure SEO standards are met.

3. Brand, Content & Communication

• Oversee the creation of marketing content — blogs, emails, social posts, brochures,

case studies, videos, and presentations.

• Maintain brand guidelines and ensure cohesive communication across the

organisation.

• Work with internal and external creative teams for design and content execution.

4. Exhibitions, Events & Offline Marketing

• Lead planning and execution of marketing for exhibitions and trade shows.

• Support stall layout planning, branding materials, and event promotions.

• Manage lead handling and coordination before, during, and after events.

5. Lead Management & CRM Collaboration

• Ensure prompt assignment of incoming leads to the respective territory managers.

• Track lead flow, progress, and campaign effectiveness.

• Work closely with the sales team to improve follow-up quality and conversion tracking.

6. Market Research & Data Management

• Conduct competitive research, pricing insights, and industry analysis.

• Prepare scraping data and market intelligence reports.

• Support management with MIS and performance dashboards.

7. Performance Analysis & Reporting

• Monitor marketing KPIs across both digital and offline activities.

• Prepare regular performance reports with insights and improvement suggestions.

• Conduct A/B tests and track results for continuous optimisation.

Requirements:

• Excellent communication, planning, and coordination skills.

• 1–5+ years of experience in a marketing role (preferably B2B).

• Strong understanding of digital marketing (PPC, SEO, analytics).

• Ability to independently manage marketing activities with high ownership.

• Proficiency in tools: Google Ads, Analytics, Search Console, MS Office, CRM systems.

• Understanding of website platforms (WordPress, CMS tools).

• Ability to manage multiple projects and meet deadlines.

Desirable Skills:

• Experience with LinkedIn, Facebook, and Instagram marketing.

• Knowledge of email marketing tools or automation platforms.

• Creative thinking and copywriting ability.

• Google certifications are an added advantage.

Qualifications:

• Degree in Marketing, Business, Communications, IT, or a related field.

Location: Vadodara

Sales and Marketing - chiller sales - chiller manufacturing company

Experience : 1-10 years

Location : Andheri,Mumbai

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.

Role & Responsibilities

About the Role:

We are seeking a highly skilled Senior Data Engineer with 5-7 years of experience to join our dynamic team. The ideal candidate will have a strong background in data engineering, with expertise in data warehouse architecture, data modeling, ETL processes, and building both batch and streaming pipelines. The candidate should also possess advanced proficiency in Spark, Databricks, Kafka, Python, SQL, and Change Data Capture (CDC) methodologies.

Key responsibilities:

Design, develop, and maintain robust data warehouse solutions to support the organization's analytical and reporting needs.

Implement efficient data modeling techniques to optimize performance and scalability of data systems.

Build and manage data lakehouse infrastructure, ensuring reliability, availability, and security of data assets.

Develop and maintain ETL pipelines to ingest, transform, and load data from various sources into the data warehouse and data lakehouse.

Utilize Spark and Databricks to process large-scale datasets efficiently and in real-time.

Implement Kafka for building real-time streaming pipelines and ensure data consistency and reliability.

Design and develop batch pipelines for scheduled data processing tasks.

Collaborate with cross-functional teams to gather requirements, understand data needs, and deliver effective data solutions.

Perform data analysis and troubleshooting to identify and resolve data quality issues and performance bottlenecks.

Stay updated with the latest technologies and industry trends in data engineering and contribute to continuous improvement initiatives.

Primary Responsibilities:

• Work in alignment with the strategic goals, vision, and mission of the company.

Market Development:

• Market mapping and identification of potential industries and companies.

• Understand and document customer product requirements

Sales Process Management:

• Conduct market visits to generate new enquiries.

• Generate and track enquiries effectively.

• Prepare quotations and follow up for approvals.

• Maintain accurate records of customer interactions.

• Review customer orders thoroughly before processing.

Commercial Documentation:

• Maintain and track all quotations.

• Prepare and update costing sheets for each enquiry.

Factory Coordination:

• Track customer orders through production to dispatch.

• Ensure timely deliveries in coordination with the factory and logistics team.

Customer Relationship Management:

• Address and track customer complaints until resolution.

• Ensure all customer documentation is complete and closed on time.

• Maintain structured reporting systems for:

• Customer follow-ups

• Sales performance

• Revenue tracking

Revenue & Collection Targets:

• Achieve total revenue targets as set by management.

• Meet machine-wise revenue targets.

• Ensure timely collection of payments and outstanding dues. 

Additional Responsibilities:

• Carry out any other tasks assigned by management from time to time based on business requirements.

If Anyone interested applied through link:- https://tiny.cc/NGtalent 

Job Description

Phonologies is seeking a Senior Data Engineer to lead data engineering efforts for developing and deploying generative AI and large language models (LLMs). The ideal candidate will excel in building data pipelines, fine-tuning models, and optimizing infrastructure to support scalable AI systems for enterprise applications.

Role & Responsibilities

• Data Pipeline Management: Design and manage pipelines for AI model training, ensuring efficient data ingestion, storage, and transformation for real-time deployment.
• LLM Fine-Tuning & Model Lifecycle: Fine-tune LLMs on domain-specific data, and oversee the model lifecycle using tools like MLFlow and Weights & Biases.
• Scalable Infrastructure: Optimize infrastructure for large-scale data processing and real-time LLM performance, leveraging containerization and orchestration in hybrid/cloud environments.
• Data Management: Ensure data quality, security, and compliance, with workflows for handling sensitive and proprietary datasets.
• Continuous Improvement & MLOps: Apply MLOps/LLMOps practices for automation, versioning, and lifecycle management, while refining tools and processes for scalability and performance.
• Collaboration: Work with data scientists, engineers, and product teams to integrate AI solutions and communicate technical capabilities to business stakeholders.

Preferred Candidate Profile

• Experience: 5+ years in data engineering, focusing on AI/ML infrastructure, LLM fine-tuning, and deployment.
• Technical Skills: Advanced proficiency in Python, SQL, and distributed data tools.
• Model Management: Hands-on experience with MLFlow, Weights & Biases, and model lifecycle management.
• AI & NLP Expertise: Familiarity with LLMs (e.g., GPT, BERT) and NLP frameworks like Hugging Face Transformers.
• Cloud & Infrastructure: Strong skills with AWS, Azure, Google Cloud, Docker, and Kubernetes.
• MLOps/LLMOps: Expertise in versioning, CI/CD, and automating AI workflows.
• Collaboration & Communication: Proven ability to work with cross-functional teams and explain technical concepts to non-technical stakeholders.
• Education: Degree in Computer Science, Data Engineering, or related field.

Perks and Benefits

• Competitive Compensation: INR 20L to 30L per year.
• Innovative Work Environment for Personal Growth: Work with cutting-edge AI and data engineering tools in a collaborative setting, for continuous learning in data engineering and AI.