Job Description

Valleysoft is a regional IT services provider delivering enterprise application development, process management, IT support, and a broad range of technology solutions for global clients. Working across the information technology and services sector, the company helps organizations solve complex business problems through practical, scalable digital solutions.

As a Data Scientist – Artificial Intelligence, you will help shape AI-driven solutions that turn data into business value. This role is focused on applying advanced data science, machine learning, and generative AI techniques to real-world challenges, partnering closely with technical teams and business stakeholders to deliver solutions that are innovative, reliable, and aligned with business goals.

Responsibilities

• Design, develop, and deploy Machine Learning and Artificial Intelligence models to address complex business challenges.
• Analyze large volumes of structured and unstructured data to identify trends, patterns, and actionable insights.
• Build predictive, classification, clustering, recommendation, and forecasting models.
• Develop and optimize Deep Learning models using modern AI frameworks.
• Design and implement Generative AI solutions using Large Language Models (LLMs).
• Build Retrieval-Augmented Generation (RAG) pipelines and apply Prompt Engineering techniques.
• Perform data collection, cleansing, preprocessing, feature engineering, and exploratory data analysis (EDA).
• Collaborate with Data Engineers and Software Engineers to build scalable AI applications and data pipelines.
• Deploy, monitor, and maintain machine learning models using MLOps best practices.
• Evaluate and improve model performance using appropriate statistical and machine learning metrics.
• Work closely with business stakeholders to translate business requirements into AI-driven solutions.
• Develop technical documentation, model documentation, and solution architecture artifacts.
• Ensure AI solutions comply with data governance, security, privacy, and Responsible AI principles.
• Stay current with emerging AI technologies, frameworks, and industry best practices.

Requirements

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Statistics, Mathematics, Engineering, or a related field.
• Min 7 years of hands-on experience in Data Science, Machine Learning, or Artificial Intelligence.
• Strong experience developing and deploying AI/ML models in enterprise environments.
• Excellent analytical, problem-solving, and communication skills.
• Experience working in Agile development environments.

Technical Skills:

Programming Languages

• Python
• SQL
• R (Preferred)

Machine Learning & Data Science

• Scikit-learn
• XGBoost
• LightGBM
• Statistical Modeling
• Predictive Analytics
• Time Series Forecasting
• Classification & Regression
• Clustering
• Recommendation Systems
• Feature Engineering

Deep Learning

• TensorFlow
• PyTorch
• Keras

Generative AI

• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation (RAG)
• LangChain
• LlamaIndex
• AI Agents
• Vector Databases (FAISS, ChromaDB, Pinecone)

IBM AI & Data Platform

• IBM watsonx.ai
• IBM watsonx.data
• IBM watsonx.governance
• IBM Cloud Pak for Data
• IBM Knowledge Catalog
• IBM Db2
• IBM SPSS Modeler (Preferred)

Data Engineering

• Apache Spark
• Hadoop
• Apache Kafka
• Apache Airflow
• Pandas
• NumPy
• ETL Pipelines

Databases

• PostgreSQL
• Oracle Database
• Microsoft SQL Server
• MongoDB

Cloud Platforms

• IBM Cloud
• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)

MLOps & DevOps

• MLflow
• Docker
• Kubernetes
• Git
• Jenkins
• CI/CD Pipelines

Data Visualization

• Power BI
• Tableau
• Matplotlib
• Plotly

Preferred Skills

• Experience developing enterprise AI solutions using IBM watsonx platform.
• Experience building AI-powered applications using LLMs and RAG architectures.
• Knowledge of Natural Language Processing (NLP) and Computer Vision.
• Experience with Explainable AI (XAI) and Responsible AI principles.
• Familiarity with Data Governance and AI Governance frameworks.
• Experience integrating AI models with REST APIs and microservices.
• Understanding of distributed computing and Big Data technologies.
• Experience working in Agile/Scrum teams.

Soft Skills

• Strong analytical and critical thinking skills.
• Excellent problem-solving abilities.
• Strong verbal and written communication skills.
• Ability to work collaboratively within cross-functional teams.
• Strong stakeholder management skills.
• Ability to manage multiple priorities in a fast-paced environment.
• Passion for innovation, continuous learning, and emerging AI technologies.

Preferred Certifications

• IBM watsonx AI Certification
• IBM AI Engineering Professional Certificate
• Microsoft Certified: Azure AI Engineer Associate
• AWS Certified Machine Learning – Specialty
• Google Professional Machine Learning Engineer
• Databricks Certified Machine Learning Professional

Benefits

• Private Health Insurance.
• Training & Development.
• Opportunities for professional growth and development in a cutting-edge field.
• A collaborative and inclusive work environment.
• The chance to work on impactful projects with a team of passionate experts.