Oneture Technologies

About the Role

We are looking for a hands-on and solution-oriented Senior Data Scientist – Generative AI to join our growing AI practice. This role is ideal for someone who thrives in designing and deploying Gen AI solutions on AWS, enjoys working with customers directly, and can lead end-to-end implementations. You will play a key role in architecting AI solutions, driving project delivery, and guiding junior team members.

Key Responsibilities

• Design and implement end-to-end Generative AI solutions for customers on AWS.
• Work closely with customers to understand business challenges and translate them into Gen AI use-cases.
• Own technical delivery, including data preparation, model integration, prompt engineering, deployment, and performance monitoring.
• Lead project execution – ensure timelines, manage stakeholder communications, and collaborate across internal teams.
• Provide technical guidance and mentorship to junior data scientists and engineers.
• Develop reusable components and reference architectures to accelerate delivery.
• Stay updated with latest developments in Gen AI, particularly AWS offerings like Bedrock, SageMaker, LangChain integrations, etc.

Required Skills & Experience

• 4–8 years of hands-on experience in Data Science/AI/ML, with at least 2–3 years in Generative AI projects.
• Proficient in building solutions using AWS AI/ML services (e.g., SageMaker, Amazon Bedrock, Lambda, API Gateway, S3, etc.).
• Experience with LLMs, prompt engineering, RAG pipelines, and deployment best practices.
• Solid programming experience in Python, with exposure to libraries such as Hugging Face, LangChain, etc.
• Strong problem-solving skills and ability to work independently in customer-facing roles.
• Experience in collaborating with Systems Integrators (SIs) or working with startups in India is a major plus.

Soft Skills

• Strong verbal and written communication for effective customer engagement.
• Ability to lead discussions, manage project milestones, and coordinate across stakeholders.
• Team-oriented with a proactive attitude and strong ownership mindset.

What We Offer

• Opportunity to work on cutting-edge Generative AI projects across industries.
• Collaborative, startup-like work environment with flexibility and ownership.
• Exposure to full-stack AI/ML project lifecycle and client-facing roles.
• Competitive compensation and learning opportunities in the AWS AI ecosystem.

About Oneture Technologies

Founded in 2016, Oneture is a cloud-first, full-service digital solutions company, helping clients harness the power of Digital Technologies and Data to drive transformations and turning ideas into business realities. Our team is full of curious, full-stack, innovative thought leaders who are dedicated to providing outstanding customer experiences and building authentic relationships. We are compelled by our core values to drive transformational results from Ideas to Reality for clients across all company sizes, geographies, and industries. The Oneture team delivers full lifecycle solutions— from ideation, project inception, planning through deployment to ongoing support and maintenance.

Our core competencies and technical expertise includes Cloud powered: Product Engineering, Big Data and AI ML. Our deep commitment to value creation for our clients and partners and “Startups-like agility with Enterprises-like maturity” philosophy has helped us establish long-term relationships with our clients and enabled us to build and manage mission-critical platforms for them.

About Oneture Technologies:

Founded in 2016, Oneture is a cloud-first, full-service digital solutions company, helping clients harness the power of Digital Technologies and Data to drive transformations and turning ideas into business realities. Our team is full of curious, full-stack, innovative thought leaders who are dedicated to providing outstanding customer experiences and building authentic relationships. We are compelled by our core values to drive transformational results from Ideas to Reality for clients across all company sizes, geographies, and industries.

Oneture team delivers full lifecycle solutions—from ideation, project inception, planning through deployment to ongoing support and maintenance. Our core competencies and technical expertise includes Cloud powered: Product Engineering, Big Data and AI ML. Our deep commitment to value creation for our clients and partners and “Startups-like agility with Enterprises-like maturity” philosophy has helped us establish long-term relationships with our clients and enabled us to build and manage mission-critical platforms for them.

About the Role

We are seeking a Data Engineer to design and maintain scalable data pipelines that power finance-related analytics and reporting. This role involves partnering closely with finance, product, and business teams to translate requirements into robust technical solutions while ensuring data accuracy, consistency, and performance.

You will work with modern data technologies—including SQL,Python, Spark, Airflow, and AWS cloud services—to build efficient workflows, optimize large-scale datasets, and deliver business-critical insights.

Role & Responsibilities

• Design, build, and maintain scalable data pipelines for finance-related datasets.
• Partner with finance stakeholders (product & business teams) to understand requirements and translate them into robust technical solutions.
• Ensure data accuracy, consistency, and timeliness across reporting layers and downstream systems.
• Optimize SQL queries and Spark jobs for large-scale datasets to improve performance and cost efficiency.
• Implement scheduling, orchestration, and monitoring of workflows using Airflow (or similar tools).
• Collaborate with cross-functional teams (Finance, Product, Analytics, Engineering) to deliver business-critical solutions.
• Adhere to best practices for coding, testing, and deployment in AWS cloud environments. 

Key Skills & Requirements

• 1.5–3 years of experience as a Data Engineer or in a related role.
• Strong proficiency in Python and SQL.
• Hands-on experience with Apache Spark (PySpark preferred).
• Experience with Airflow (or other orchestration tools).
• Working knowledge of AWS services (S3, EMR, Glue, Redshift, etc.).
• Strong problem-solving skills with the ability to convert business needs into technical solutions.
• Effective communication skills to collaborate with both technical and non-technical stakeholders.

Good to Have

• Experience with Delta Lake / Data Lake architectures.
• Knowledge of CI/CD, DevOps practices, and observability tools.
• Exposure to SAP RISE environments.

About the Role

We are looking for a highly skilled Machine Learning Lead with proven expertise in demand forecasting to join our team. The ideal candidate will have 4-8 years of experience building and deploying ML models, strong knowledge of AWS ML services and MLOps practices, and the ability to lead a team while working directly with clients. This is a client-facing role that requires strong communication skills, technical depth, and leadership ability.

Key Responsibilities

• Lead end-to-end design, development, and deployment of demand forecasting models.
• Collaborate with clients to gather requirements, define KPIs, and translate business needs into ML solutions.
• Architect and implement ML workflows using AWS ML ecosystem (SageMaker, Bedrock, Lambda, S3, Step Functions, etc.).
• Establish and enforce MLOps best practices for scalable, reproducible, and automated model deployment and monitoring.
• Mentor and guide a team of ML engineers and data scientists, ensuring technical excellence and timely delivery.
• Partner with cross-functional teams (engineering, data, business) to integrate forecasting insights into client systems.
• Present results, methodologies, and recommendations to both technical and non-technical stakeholders.
• Stay updated with the latest advancements in forecasting algorithms, time-series modeling, and AWS ML offerings.

Required Skills & Experience

• 4-8 years of experience in machine learning with a strong focus on time-series forecasting and demand prediction.
• Hands-on experience with AWS ML stack (Amazon SageMaker, Step Functions, Lambda, S3, Athena, CloudWatch, etc.).
• Strong understanding of MLOps pipelines (CI/CD for ML, model monitoring, retraining workflows).
• Proficiency in Python, SQL, and ML libraries (TensorFlow, PyTorch, Scikit-learn, Prophet, GluonTS, etc.).
• Experience working directly with clients and stakeholders to understand business requirements and deliver ML solutions.
• Strong leadership and team management skills, with the ability to mentor and guide junior team members.
• Excellent communication and presentation skills for both technical and business audiences.

Preferred Qualifications

• Experience with retail, FMCG, or supply chain demand forecasting use cases.
• Exposure to generative AI and LLMs for augmenting forecasting solutions.
• AWS Certification (e.g., AWS Certified Machine Learning – Specialty).

What We Offer

• Opportunity to lead impactful demand forecasting projects with global clients.
• Exposure to cutting-edge ML, AI, and AWS technologies.
• Collaborative, fast-paced, and growth-oriented environment.
• Competitive compensation and benefits.