Data Scientist

Company Overview

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.

Role Overview

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.
Minimum 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 and 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.

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