Oneture Technologies
https://oneture.comAbout
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, Bigdata 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.
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Jobs at Oneture Technologies
Data ScienceAbout 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.
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Job Overview
We are looking for a Data Engineer to join our data team to solve data-driven critical
business problems. The hire will be responsible for expanding and optimizing the existing
end-to-end architecture including the data pipeline architecture. The Data Engineer will
collaborate with software developers, database architects, data analysts, data scientists and platform team on data initiatives and will ensure optimal data delivery architecture is
consistent throughout ongoing projects. The right candidate should have hands on in
developing a hybrid set of data-pipelines depending on the business requirements.
Responsibilities
- Develop, construct, test and maintain existing and new data-driven architectures.
- Align architecture with business requirements and provide solutions which fits best
- to solve the business problems.
- Build the infrastructure required for optimal extraction, transformation, and loading
- of data from a wide variety of data sources using SQL and Azure ‘big data’
- technologies.
- Data acquisition from multiple sources across the organization.
- Use programming language and tools efficiently to collate the data.
- Identify ways to improve data reliability, efficiency and quality
- Use data to discover tasks that can be automated.
- Deliver updates to stakeholders based on analytics.
- Set up practices on data reporting and continuous monitoring
Required Technical Skills
- Graduate in Computer Science or in similar quantitative area
- 1+ years of relevant work experience as a Data Engineer or in a similar role.
- Advanced SQL knowledge, Data-Modelling and experience working with relational
- databases, query authoring (SQL) as well as working familiarity with a variety of
- databases.
- Experience in developing and optimizing ETL pipelines, big data pipelines, and datadriven
- architectures.
- Must have strong big-data core knowledge & experience in programming using Spark - Python/Scala
- Experience with orchestrating tool like Airflow or similar
- Experience with Azure Data Factory is good to have
- Build processes supporting data transformation, data structures, metadata,
- dependency and workload management.
- Experience supporting and working with cross-functional teams in a dynamic
- environment.
- Good understanding of Git workflow, Test-case driven development and using CICD
- is good to have
- Good to have some understanding of Delta tables It would be advantage if the candidate also have below mentioned experience using
- the following software/tools:
- Experience with big data tools: Hadoop, Spark, Hive, etc.
- Experience with relational SQL and NoSQL databases
- Experience with cloud data services
- Experience with object-oriented/object function scripting languages: Python, Scala, etc.
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