Associate Data Scientist

Posted 3 Days Ago
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Bangalore, Bengaluru Urban, Karnataka, IND
Hybrid
Mid level
Artificial Intelligence • Big Data • Marketing Tech • Consulting
The Role
Develops and deploys forecasting, optimization, machine learning, and generative AI solutions for client business problems. Responsibilities include model ownership, project scoping, data and scenario analysis, stakeholder presentations, cloud performance collaboration, and mentoring junior colleagues. The role requires expertise in Python, SQL, optimization, supply chain analytics, cloud platforms, machine learning model evaluation, and business communication.
Summary Generated by Built In

Metyis is growing! We are looking for a Associate Data Scientist with 3 - 7 years of experience for a full-time position to join our Data and Analytics team in Bangalore

Who we are

The next step of your career starts here, where you can bring your own unique mix of skills and perspectives to a fast-growing team.

Metyis is a global and forward-thinking firm operating across a wide range of industries, developing and delivering AI & Data, Digital Commerce, Marketing & Design solutions and Advisory services. At Metyis, our long-term partnership model brings long-lasting impact and growth to our business partners and clients through extensive execution capabilities.

With our team, you can experience a collaborative environment with highly skilled multidisciplinary experts, where everyone has room to build bigger and bolder ideas. Being part of Metyis means you can speak your mind and be creative with your knowledge. Imagine the things you can achieve with a team that encourages you to be the best version of yourself.

We are Metyis. Partners for Impact.

What we offer 
  • Enjoy a high level of responsibility and immediate client interactions under the guidance of senior team members.

  • Interact with data team on regular basis to drive innovation and create impact on our clients

  • Help our clients to target, measure and improve mission-critical business metrics and generate demonstrable return on investment.

  • Become part of a fast-growing international and diverse team

What you will do

Metyis is growing! We are looking for a data professional to join our Data Science team.

  • Own live forecasting and optimization models, keeping them accurate and adapting them as constraints and business rules change.

  • Scope and develop new data science projects end to end, from problem framing to deployment.

  • Apply machine learning and generative AI to extend solutions where they add value.

  • Answer client business questions using data & scenario analyses and provide clear recommendations.

  • Present results to client stakeholders, including senior management.

  • Work with data and engineering teams on data quality, deployment and cloud performance.

  • Guide junior colleagues and review their work.

What you will bring

  • 3–6 years of professional experience in data science or advanced analytics, delivering projects for business stakeholders.

  • Business acumen: you can connect data science model outputs and data analysis to business processes (related to functions such as cost, service, inventory, delivery etc.) and communicate insights & recommendations clearly to business stakeholders in English.

  • Strong Python (pandas, scikit-learn), SQL and Git; you can debug and improve someone else's code.

  • Optimization: a solid grasp of optimization concepts, such as objectives, constraints and trade-offs, and experience configuring optimization tools and interpreting their results.

  • Supply chain: working knowledge of demand forecasting, inventory and replenishment, and KPIs such as forecast accuracy and service level.

  • Cloud: experience running data and ML workloads on Azure, AWS or GCP, ideally with Databricks or Spark.

  • Machine learning: hands-on experience building and deploying models, such as gradient boosting and time series forecasting, with scikit-learn, XGBoost or LightGBM, including evaluation and drift monitoring.

  • Generative AI: practical exposure to generative AI and a good sense of where it can add value to business processes.

  • A degree in a quantitative field, such as engineering, statistics, computer science or operations research.

    Nice to have

  • MLOps tooling, such as MLflow, Docker and CI/CD.

  • Orchestration tools, such as Airflow or Azure Data Factory.

  • Experience with logistics, pricing or S&OP analytics.

  • Consulting or other client-facing experience.

We are united by our differences

At Metyis, we are driven by curiosity and collaboration. We value diversity, equity, inclusion, and belonging (DEIB) in all its forms as it makes us stronger as an organisation and promotes creativity and innovation. We welcome all talents and are committed to creating a workplace where every employee can make a meaningful impact and grow.

Recruitment Disclaimer

Metyis only contacts candidates through verified and official channels: LinkedIn (official and verified recruiter profiles), emails ending in @metyis.com, and our Applicant Tracking System (Recruitee). We do not use WhatsApp, social media messaging platforms, or personal accounts for recruitment outreach. If you receive suspicious communication claiming to be from Metyis, please verify the sender and report it through our official website.

Skills Required

  • 3-6 years of professional experience in data science or advanced analytics delivering projects for business stakeholders
  • Business acumen and ability to connect data science outputs to business processes and communicate recommendations clearly in English
  • Strong Python experience with pandas and scikit-learn
  • Strong SQL and Git skills, including debugging and improving existing code
  • Understanding of optimization concepts, including objectives, constraints, and trade-offs
  • Experience configuring optimization tools and interpreting results
  • Working knowledge of demand forecasting, inventory, replenishment, and supply chain KPIs
  • Experience running data and machine learning workloads on Azure, AWS, or GCP
  • Hands-on experience building and deploying machine learning models, including gradient boosting and time series forecasting
  • Experience with scikit-learn, XGBoost, or LightGBM, including model evaluation and drift monitoring
  • Practical exposure to generative AI and understanding of its business applications
  • Degree in a quantitative field such as engineering, statistics, computer science, or operations research
  • Experience with Databricks or Spark
  • Experience with MLOps tools such as MLflow, Docker, and CI/CD
  • Experience with orchestration tools such as Airflow or Azure Data Factory
  • Experience with logistics, pricing, or S&OP analytics
  • Consulting or other client-facing experience

Metyis Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Metyis and has not been reviewed or approved by Metyis.

  • Leave & Time Off Breadth — Paid time off is described as aligning with local competitive practices in European hubs, with the UK example citing around 25 days of annual leave. This points to a solid, region-appropriate leave structure.
  • Wellbeing & Lifestyle Benefits — Wellness activities like yoga and Pilates, plus workshops and a supportive environment, are highlighted alongside development offerings. These elements indicate attention to lifestyle and wellbeing beyond core pay.
  • Pay Growth & Progression — Compensation philosophy emphasizes rapid career progression and fast-tracked responsibilities, with indications of long-term growth potential. Some roles and regions are described as offering competitive base pay, reinforcing advancement pathways.

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The Company
HQ: Baar
776 Employees
Year Founded: 2013

What We Do

Metyis is a global firm that specializes in AI & Data, Digital Commerce, Marketing, and Design solutions, alongside advisory services. They focus on long-term partnerships to drive sustainable growth and performance for their clients through data-driven decision-making and integrated digital strategies, operating with a diverse, global talent pool across multiple international locations.

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