QuaXigma IT solutions Private Limited

Data Scientist

Job Id: QX003

About Us:

QX impact was launched with a mission to make AI accessible and affordable and deliver AI Products/Solutions at scale for enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights, businesses will continue to face challenges to better understand their customers and even lose them; Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Position Overview:

We are seeking a collaborative and analytical Data Scientist who can bridge the gap between business needs and data science capabilities. In this role, you will lead and support projects that apply machine learning, AI, and statistical modeling to generate actionable insights and drive business value.

Key Responsibilities:

• Collaborate with stakeholders to define and translate business challenges into data science solutions.
• Conduct in-depth data analysis on structured and unstructured datasets.
• Build, validate, and deploy machine learning models to solve real-world problems.
• Develop clear visualizations and presentations to communicate insights.
• Drive end-to-end project delivery, from exploration to production.
• Contribute to team knowledge sharing and mentorship activities.

Must-Have Skills:

• 3+ years of progressive experience in data science, applied analytics, or a related quantitative role, demonstrating a proven track record of delivering impactful data-driven solutions.
• Exceptional programming proficiency in Python, including extensive experience with core libraries such as Pandas, NumPy, Scikit-learn, NLTK and XGBoost. 
• Expert-level SQL skills for complex data extraction, transformation, and analysis from various relational databases.
• Deep understanding and practical application of statistical modeling and machine learning techniques, including but not limited to regression, classification, clustering, time series analysis, and dimensionality reduction.
• Proven expertise in end-to-end machine learning model development lifecycle, including robust feature engineering, rigorous model validation and evaluation (e.g., A/B testing), and model deployment strategies.
• Demonstrated ability to translate complex business problems into actionable analytical frameworks and data science solutions, driving measurable business outcomes.
• Proficiency in advanced data analysis techniques, including Exploratory Data Analysis (EDA), customer segmentation (e.g., RFM analysis), and cohort analysis, to uncover actionable insights.
• Experience in designing and implementing data models, including logical and physical data modeling, and developing source-to-target mappings for robust data pipelines.
• Exceptional communication skills, with the ability to clearly articulate complex technical findings, methodologies, and recommendations to diverse business stakeholders (both technical and non-technical audiences).
• Experience in designing and implementing data models, including logical and physical data modeling, and developing source-to-target mappings for robust data pipelines.
• Exceptional communication skills, with the ability to clearly articulate complex technical findings, methodologies, and recommendations to diverse business stakeholders (both technical and non-technical audiences).

Good-to-Have Skills:

• Experience with cloud platforms (Azure, AWS, GCP) and specific services like Azure ML, Synapse, Azure Kubernetes and Databricks.
• Familiarity with big data processing tools like Apache Spark or Hadoop.
• Exposure to MLOps tools and practices (e.g., MLflow, Docker, Kubeflow) for model lifecycle management.
• Knowledge of deep learning libraries (TensorFlow, PyTorch) or experience with Generative AI (GenAI) and Large Language Models (LLMs).
• Proficiency with business intelligence and data visualization tools such as Tableau, Power BI, or Plotly.
• Experience working within Agile project delivery methodologies.

Competencies:

·        Tech Savvy - Anticipating and adopting innovations in business-building digital and technology applications.

·        Self-Development - Actively seeking new ways to grow and be challenged using both formal and informal development channels.

·        Action Oriented - Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.

·        Customer Focus - Building strong customer relationships and delivering customer-centric solutions.

·        Optimizes Work Processes - Knowing the most effective and efficient processes to get things done, with a focus on continuous improvement.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Role Summary:

We are looking for a Marketing Specialist who understands both AI technology and the industrial manufacturing landscape. This person will be responsible for driving awareness, generating demand, and positioning our AI solutions as a critical tool for modern manufacturing.

Key Responsibilities:

• Develop and execute B2B marketing strategies to promote AI products tailored for the manufacturing sector.
• Craft messaging, positioning, and value propositions based on a deep understanding of manufacturing challenges and AI capabilities.
• Create high-impact content: case studies, product briefs, whitepapers, videos, webinars, and customer success stories.
• Work closely with product, sales, and data science teams to translate complex features into customer-focused benefits.
• Plan and manage industry-specific campaigns using digital marketing, email outreach, LinkedIn, and webinars.
• Represent the brand at manufacturing tech expos, webinars, and customer demos.
• Analyze campaign performance and optimize marketing efforts based on data-driven insights.
• Support lead generation and ABM (Account-Based Marketing) activities focused on key enterprise clients.

Required Skills & Qualifications:

• Bachelor's or Master’s in Marketing, Engineering, Business, or related field.
• 3+ years of experience in B2B marketing, ideally in SaaS, AI/ML products, or industrial/manufacturing tech.
• Strong understanding of the manufacturing domain (automotive, steel, FMCG, pharma, etc.).
• Familiarity with AI/ML concepts such as predictive maintenance, anomaly detection, computer vision, digital twins, etc.
• Proficiency in content marketing, digital campaigns, SEO/SEM, and marketing automation tools (e.g., HubSpot, Marketo).
• Excellent written and verbal communication skills with the ability to convey technical concepts in a simple, compelling manner.
• Ability to analyze data, track KPIs, and continuously improve marketing performance.

Preferred:

• Experience in working with data-driven platforms or IIoT (Industrial Internet of Things).
• Exposure to CRM systems like Salesforce.
• Knowledge of analytics tools such as Google Analytics, Power BI, or Tableau.
• Experience collaborating with cross-functional teams including data scientists, engineers, and sales.

Senior Generative AI Engineer

Job Id: QX016

About Us:

The QX impact was launched with a mission to make AI accessible and affordable and deliver AI Products/Solutions at scale for the enterprises by bringing the power of Data, AI, and Engineering to drive digital transformation. We believe without insights; businesses will continue to face challenges to better understand their customers and even lose them.

Secondly, without insights businesses won't’ be able to deliver differentiated products/services; and finally, without insights, businesses can’t achieve a new level of “Operational Excellence” is crucial to remain competitive, meeting rising customer expectations, expanding markets, and digitalization.

Job Summary:

We seek a highly experienced Senior Generative AI Engineer who focus on the development, implementation, and engineering of Gen AI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Senior Gen AI engineer will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.

Responsibilities:

·        Build GenAI solutions such as virtual assistant, data augmentation, automated insights and predictive analytics

·        Design, develop, and fine-tune generative AI models (GANs, VAEs, Transformers).

·        Handle data preprocessing, augmentation, and synthetic data generation.

·        Work with NLP, text generation, and contextual comprehension tasks.

·        Develop backend services using Python or .NET for LLM-powered applications.

·        Build and deploy AI applications on cloud platforms (Azure, AWS, GCP).

·        Optimize AI pipelines and ensure scalability.

·        Stay updated with advancements in AI and ML.

Skills & Requirements:

• Strong knowledge of machine learning, deep learning, and NLP.
• Proficiency in Python, TensorFlow, PyTorch, and Keras.
• Experience with cloud services, containerization (Docker, Kubernetes), and AI model deployment.
• Understanding of LLMs, embeddings, and retrieval-augmented generation (RAG).
• Ability to work independently and as part of a team.
• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related field.
• 6+ years of experience in Gen AI, or related roles.
• Experience with AI/ML model integration into data pipelines.

Core Competencies for Generative AI Engineers:

1.      Programming & Software Development

a.      Python – Proficiency in writing efficient and scalable code with strong knowledge with NumPy, Pandas, TensorFlow, PyTorch and Scikit-learn.

b.      LLM Frameworks – Experience with Hugging Face Transformers, LangChain, OpenAI API, and similar tools for building and deploying large language models.

c.      API integration such as FastAPI, Flask, RESTful API, WebSockets or Django.

d.      Knowledge of Version Control, containerization, CI/CD Pipelines and Unit Testing.

2.      Vector Database & Cloud AI Solutions

a.      Pinecone, FAISS, ChromaDB, Neo4j

b.      Azure Redis/ Cognitive Search

c.      Azure OpenAI Service

d.      Azure ML Studio Models

e.      AWS (Relevant Services)

3.      Data Engineering & Processing

1. Handling large-scale structured & unstructured datasets.
2. Proficiency in SQL, NoSQL (PostgreSQL, MongoDB), Spark, and Hadoop.
3. Feature engineering and data augmentation techniques.

4.      NLP & Computer Vision

1. NLP: Tokenization, embeddings (Word2Vec, BERT, T5, LLaMA).
2. CV: Image generation using GANs, VAEs, Stable Diffusion.
3. Document Embedding – Experience with vector databases (FAISS, ChromaDB, Pinecone) and embedding models (BGE, OpenAI, SentenceTransformers).
4. Text Summarization – Knowledge of extractive and abstractive summarization techniques using models like T5, BART, and Pegasus.
5. Named Entity Recognition (NER) – Experience in fine-tuning NER models and using pre-trained models from SpaCy, NLTK, or Hugging Face.
6. Document Parsing & Classification – Hands-on experience with OCR (Tesseract, Azure Form Recognizer), NLP-based document classifiers, and tools like LayoutLM, PDFMiner.

5.      Model Deployment & Optimization

1. Model compression (quantization, pruning, distillation).
2. Deployment using Azure CI/CD, ONNX, TensorRT, OpenVINO on AWS, GCP.
3. Model monitoring (MLflow, Weights & Biases) and automated workflows (Azure Pipeline).
4. API integration with front-end applications.

6.      AI Ethics & Responsible AI

1. Bias detection, interpretability (SHAP, LIME), and security (adversarial attacks).

7.      Mathematics & Statistics

1. Linear Algebra, Probability, and Optimization (Gradient Descent, Regularization, etc.).

8.      Machine Learning & Deep Learning

a.      Expertise in supervised, unsupervised, and reinforcement learning.

a.      Proficiency in TensorFlow, PyTorch, and JAX.

b.      Experience with Transformers, GANs, VAEs, Diffusion Models, and LLMs (GPT, BERT, T5).

Personal Attributes:

• Strong problem-solving skills with a passion for data architecture.
• Excellent communication skills with the ability to explain complex data concepts to non-technical stakeholders.
• Highly collaborative, capable of working with cross-functional teams.
• Ability to thrive in a fast-paced, agile environment while managing multiple priorities effectively.

Why Join Us?

• Be part of a collaborative and agile team driving cutting-edge AI and data engineering solutions.
• Work on impactful projects that make a difference across industries.
• Opportunities for professional growth and continuous learning.
• Competitive salary and benefits package.

Ready to make an impact? Apply today and become part of the QX impact team!