Lead Data Scientist

  • Full-time
  • Salary Min - India: 3,000,000
  • Salary Max - India: 4,500,000
  • Posting Location: Bangalore, India

Company Description

OUR STORY

Let’s be honest: there are lots of people out there doing what we do. We’re just not convinced they’re doing it right. Businesses are hungry for innovation and opportunity, but not at the cost of their independence. At Ollion, we’ve connected companies and capabilities around the world to help ambitious organizations make the most of their transformation and leave the status quo in the dust.

WORKING AT OLLION

Innovation is risky. It demands bold steps and big questions, but that’s the price of making change. We’ve got our head in the cloud and two feet on the ground, channeling tech’s endless potential towards a single goal: making a world of difference. And we’re building a global team to do just that— a team capable of making game-changing breakthroughs without ever losing sight of the people it will impact. This is more than consulting. This is the change you can be.

THE OLLION DIFFERENCE

At Ollion, we’re all in on your independence. Our teams are seasoned. Our solutions are straightforward—sometimes even groundbreaking. And our engagements? Exactly as long as you want them to be. We deliver fresh thinking and hard-earned insight in a way that works for you and your customers, arming your organization with everything you need to make your transformation truly mean something.

WORKING WITH OLLION (our clients’ experiences)

Progress matters more than process. Our global team of cloud-native pros is all about creating new and better ways to work—not just by solving your tech challenges, but by using technology to solve your business challenges. We keep the formulas, frameworks, and ten-point plans to a minimum, tackling your most pressing problems with a proprietary mix of good-old-fashioned ingenuity and refreshing humanity.

DIVERSITY AT OLLION 

One of our cultural keystones, ‘Find the angle’ recognizes that every individual has different aspirations, needs and brings a unique perspective. 

We value diversity, inclusion, and equity (DE&I) as core to our success. We believe that a diverse workforce brings together unique perspectives, experiences, and ideas, leading to innovation, creativity, and better outcomes for our clients and our organization. We are on a journey and are committed to building a workplace that celebrates and respects individuals from all backgrounds, including but not limited to race, ethnicity, gender, sexual orientation, age, disability, and cultural heritage.  

As our commitment to diversity and inclusion is reflected in our: 

  • Awareness and sensitisation programs: to create awareness and sensitisation. We encourage open dialogue, active listening, and mutual respect, creating a safe and supportive environment for everyone to contribute their unique perspectives and ideas. 
  • Dedicated efforts to building diverse teams: that leverage the strength of our differences to tackle complex challenges and drive innovation. By embracing diversity, we broaden our collective knowledge, enhance problem-solving capabilities, and unlock limitless potential for our employees.

Job Description

As a Lead Data Scientist, you will play a pivotal role in leading the development and deployment of advanced machine learning models and generative AI solutions for our clients. You will be responsible for designing, implementing, and optimizing data science projects from inception to deployment, using state-of-the-art cloud-native technologies on AWS and GCP. This role requires a strong focus on MLOps, ensuring efficient model lifecycle management and integration into business processes.

Key Responsibilities:

• Lead and Manage Data Science Projects: Oversee the end-to-end lifecycle of data science projects, from data preprocessing, model development, model deployment and monitoring on the cloud

• Develop Machine Learning Models: Design, build, and deploy complex machine learning models and generative AI solutions that address client-specific business challenges.

• Implement MLOps Practices: Establish robust MLOps pipelines and frameworks to automate, monitor, and optimize model deployment, retraining, and scalability using cloud-native tools and platforms.

• Collaborate with Cross-functional Teams: Work closely with data engineers, software developers, and domain experts to ensure seamless integration of data science solutions within the client’s ecosystem.

• Client Engagement: Act as a subject matter expert in client meetings, presentations, and workshops, providing insights and recommendations on machine learning and AI strategies.

• Stay Current with Industry Trends: Continuously monitor advancements in machine learning, generative AI, and cloud technologies, incorporating relevant innovations into projects.

• Mentor and Develop Talent: Provide technical leadership and mentorship to junior data scientists and team members, fostering a culture of continuous learning and innovation.

Qualifications

Technical Expertise:

• Proven experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn) and generative AI models (e.g., GPT, DALL-E, diffusion models).

• Strong proficiency in Python and relevant data science libraries (e.g., NumPy, Pandas, SciPy).

• Experience with ML frameworks on the cloud:
              GCP: Vertex AI, Vertex AI pipelines

              AWS: SageMaker, Sagemaker Studio

• Demonstrated expertise in deploying and maintaining machine learning models in production environments.

• MLOps Knowledge: Deep understanding of the machine learning lifecycle, including model versioning, monitoring, retraining, and CI/CD for machine learning workflows.

• Data Engineering Skills: Familiarity with data engineering concepts, such as ETL pipelines, data warehousing, and data lakes.

• Analytical Thinking: Strong analytical and problem-solving skills, with the ability to work on complex and ambiguous problems.

• Communication Skills: Excellent communication and presentation skills, with the ability to convey complex technical concepts to non-technical stakeholders.

• Leadership: Proven experience leading data science teams and projects in a fast-paced consulting or client-facing environment.

Qualifications:

• Experience: Minimum 5 years of hands-on experience in data science, with a strong focus on machine learning, generative AI, and MLOps.

• Education: Master’s or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Additional Information

BENEFITS & PERKS FOR WORKING AT OLLION

Our employees multiply their potential because they have opportunities to: Create a lasting Impact, Learn and Grow professionally & personally, Experience great Culture, and Be your Whole Self!

Beyond an amazing, collaborative work environment, great people, and inspiring, innovative work, we have some great benefits and perks:

  • Benchmarked, competitive, in-market total rewards package including (but not limited to): base salary & short-term incentive for all employees
  • Fully remote-first, small but Global organization; ‘learn wherever, whenever’ frees our people from a rigid view of learning and growth
  • Retirement planning (i.e. CPF, EPF, company-matched 401(k))
  • Globally, we build benefit plans that offer choices for whatever stage in life our employees are in and allow for flexibility as life happens.  Employees have access to a fully comprehensive benefits package to choose the medical, dental, and vision insurance plan that best fits their lives. In addition to great healthcare coverage, we also offer all employees mental health resources and additional wellness programs.
  • Generous time off and leave allowances
  • And more!

Ollion is an equal opportunity employer. We celebrate diversity and we are committed to creating an inclusive environment for all employees. Ollion does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, parental status, military service, or other non-merit factor.