Sr. Data Scientist

About OnlineSales.ai  
Built by ex-Amazon ad-tech experts, OnlineSales.ai offers a future-proof Retail Media Operating System - boosting Retailer’s profitability by 7% of Sales! We are an Enterprise B2B SaaS startup, based out of Pune India. With OnlineSales.ai's platform, Retailers activate and delight 10x more Brands by offering an omni-channel media buying experience, advanced targeting, analytics & 2x better ROAS. Tier 1 Retailers and Marketplaces globally are accelerating their Monetization strategy with OnlineSales.ai and are innovating ahead of the market by at least 2 years.

About the Role

At Onlinesales.ai, your ability to navigate the complexities of building scalable and high-performance systems, combined with your data science skills, will make you an invaluable contributor to our mission.

We are seeking a highly motivated Data Scientist who is passionate about unlocking the potential of big datasets. As a key member of our team, you will play a vital role in mining and analyzing large volumes of data, deriving actionable insights, and building predictive models that have a direct impact on our business. If you are driven by the opportunity to make a difference through data-driven decision-making, this position is perfect for you.

What will you do @OnlineSales?

• Analytical Translation: Translate complex business problems into sophisticated analytical structures, conceptualising solutions anchored in statistical and machine learning methodologies.

• Problem Solving: While technical proficiency in data manipulation, statistical modelling, and machine learning is crucial, the ability to apply these skills to solve real-world business problems is equally vital.

• Technical Proficiencies:

• Data Preparation: You would be responsible for understanding the available data specific to the ad server and retail media and conducting thorough data preprocessing. By ensuring data quality and reliability, you will lay the foundation for accurate and effective ML algorithms tailored to the needs of the retail media domains.

• Feature Engineering:  This might involve transforming variables specific to advertising campaigns, creating new features that capture important metrics, or applying dimensionality reduction techniques that extract meaningful insights.

• Model Selection: Based on the requirements of retail media domains, you will evaluate different ML algorithms to identify the most suitable ones. This evaluation would involve considering algorithms such as regression models, decision trees, random forests, gradient boosting, or even deep learning models like neural networks. You will assess their performance using domain-specific evaluation metrics such as click-through rate (CTR), conversion rate, customer engagement, or return on ad spend (ROAS).

• Model Training and Evaluation: Once the ML algorithms are selected, you will train them using the prepared data, employing appropriate techniques such as cross-validation specific to ad-serving and retail media. You will fine-tune the model hyperparameters to optimize performance for key metrics like CTR or ROAS.

• Model Deployment: This involves integrating the ML models with the existing ad-serving infrastructure and retailer media platforms, ensuring their scalability and performance.

• Model Maintenance and Monitoring: ML models used in the ad-server and retail media domains require continuous monitoring and maintenance to ensure their ongoing effectiveness. You would implement mechanisms to track model performance, detect concept drift specific to ad-serving and media trends, and proactively update the models as necessary.

• Driving Innovation with AI/ML knowledge :

• Lead the design, development, and deployment of advanced machine learning and deep learning solutions with a strong focus on Large Language Models (LLMs) and Generative AI (GenAI).

• Build scalable systems and pipelines for training, fine-tuning, evaluating, and serving LLMs across a variety of business use cases (e.g., content generation, summarization, semantic search, personalization, etc.).

• Drive experimentation and innovation by applying cutting-edge GenAI research to real-world problems, ensuring models are production-ready and meet high performance and reliability standards.

• Collaborate closely with product, engineering, and research teams to integrate LLM-powered features into customer-facing applications, with a focus on performance, security, and cost optimization.

• Analyze large-scale datasets to extract meaningful insights and continuously improve model accuracy, relevance, and fairness.

• Stay ahead of industry trends in GenAI, foundation models, and multimodal AI, and bring that expertise into technical strategy and roadmap planning.

• Mentor and guide junior data scientists and contribute to best practices in model development, MLOps, and responsible AI.

• Cross-Functional Collaboration: Collaborate seamlessly with multiple teams, including Consulting and Engineering, fostering relationships with diverse stakeholders to meet deadlines and bring Analytical Solutions to life.

• Lead cross-functional teams of Data Scientists and Data Analysts to deliver impactful AI/ML and analytics solutions aligned with business goals.

• Provide technical and strategic leadership for the design, development, and deployment of scalable machine learning systems, with a strong focus on Large Language Models (LLMs) and Generative AI (GenAI).

By applying your expertise in data science to the ad-server and retail media domains, you will contribute to delivering targeted and impactful advertising campaigns, optimizing ad inventory, and maximizing ROI for OnlineSales.ai and its clients.

You will be a great fit, if you have:

• A master's or doctoral degree in a relevant field such as computer science, statistics, mathematics, or data science is preferred. A strong academic background with coursework in machine learning, statistical modeling, data mining, and programming is valuable.

• 6+ years of practical experience in data science, generative AI, machine learning, and analytics. Experience in relevant domains, such as e-commerce, advertising, or retail, may be advantageous.

• Team Management: At least 2+ years' experience in managing teams of Data Scientists and Data analysts

• Advanced Proficiency in Python is essential for data manipulation, statistical analysis, and machine learning model development. 

• Senior data scientists should have a solid understanding of various machine learning algorithms, statistical techniques, and data visualization tools. 

• Experience with big data technologies, cloud platforms (GCP preferred), and distributed computing frameworks is valuable for handling large-scale datasets.

• Problem-Solving and Analytical Skills: you would get to work on some interesting ML/NLP problem statements such as improving “Search Relevancy for our ad servers” or “figuring out new AL use cases in ad tech domain” and you will also get to understand how your work ultimately creates positive business impact by improving client performance metrics.

• As senior members of the team, data scientists are often expected to lead and mentor junior members, collaborate with cross-functional teams, and communicate effectively with stakeholders. Strong interpersonal and communication skills are vital for presenting findings, explaining complex concepts to non-technical audiences, and influencing decision-making.

• Should have a deep understanding of the business context and objectives. You should be able to translate business problems into analytical questions and provide strategic recommendations based on data insights. Familiarity with key performance indicators (KPIs), revenue models, and marketing metrics is beneficial.

• Given the rapidly evolving field of data science, senior data scientists should demonstrate a commitment to continuous learning. Staying updated with the latest research, methodologies, and tools is essential for keeping their skills relevant and for driving innovation within the organization.

Why OnlineSales.ai?

• Startup-y. We believe Startup is a mindset. It’s about being scrappy, being nimble, solving tough problems with constrained resources, and more. It’s about working hard and playing hard

• Enterprise SaaS. Opportunity to work with an Enterprise Product SaaS firm with aspirations of growing 10x across the globe

• AI-led Retail Tech. We are working to digitize & democratize one of the most exciting and growing verticals - Retail Tech leveraging data, machine learning, and automation (culmination of ad-tech, mar-tech, and analytics for Retail vertical)

• Meaningful work. This is not just a job. You can find a job anywhere. This is a place for the bold to get paid who make a real impact on business

• No red tape. Say goodbye to pointless meetings or political hoops to jump through. We’re scrappy, believe in autonomy, and empower our teams to do whatever it takes to do the unthinkable

• Problem Solving. We ignite the best in you. We exist not only to deliver meaningful innovation but to ignite and inspire the creative problem-solver in you

• Quirky & fun. Enjoy new skills and hobbies like being a quiz master, playing board games, trying your hands on percussion, playing Djembe, and spreading love within the org!