About the Company: Aria’s Science Lab is a cutting-edge AI company that specializes in building scalable AI solutions for its clients in various domains. As we continue to scale, we need a hands-on HR Ops & Talent Manager to help us find and retain top-tier talent in the rapidly evolving tech space. About the Role: Are you passionate about building high-performing teams and shaping company culture in a cutting-edge Data Science & AI startup? At Aria’s Science Lab, we're on a mission to transform industries with our innovative AI solutions, and we’re looking for an experienced HR Ops & Talent Manager to join our growing team! Responsibilities: HR Operations: Own and manage end-to-end HR processes: onboarding, offboarding, documentation, policy execution, HRIS, and compliance Align global people policies to Indian legal, cultural, and operational contexts Partner with Finance and Legal on contracts, payroll inputs, and audits Maintain accuracy and transparency in all employee data and lifecycle workflows Talent Programs: Design and implement structured performance review cycles, including 360° feedback processes Develop internal career growth paths, learning frameworks, and upskilling programs tailored for AI and product teams Support succession planning and internal mobility aligned to strategic growth goals Talent Acquisition Support: Collaborate with hiring managers and external partners on role scoping and candidate assessment Conduct initial HR screenings, assess for value and culture alignment Maintain a strong understanding of technical hiring trends and talent ecosystems, especially in AI, Data Science, and Engineering People Engagement: Serve as a partner to team leads on people-related decisions, engagement health, and team dynamics Be a point of contact for employee concerns, conflict resolution, and people advisory Contribute to building a cohesive, high-performing, and inclusive culture Qualifications: Proven track record (3-5 years of experience): Proven expertise across all facets of HR, including but not limited to - HR operations, policy implementation, talent programs, employee relations, and recruitment Expertise in Recruiting Technical Talent: Strong background in recruiting for specialized technical roles (e.g., data scientists, machine learning engineers, AI researchers). Startup Experience: Progressive HR experience in product-first companies, preferably with exposure to AI or deep-tech environments People-Oriented: Passion for helping people grow, both personally and professionally. You’re a strategic thinker but also love being hands-on. Strong Communication & Negotiation Skills: Ability to effectively communicate with leadership, hiring managers, and candidates. Skilled at negotiating offers and building relationships. Cultural Fit: Ability to thrive in a startup environment, where flexibility, agility, and a collaborative spirit are key. Required Skills: Strong background in HR operations and talent management Experience in technical recruitment and understanding of AI and Data Science roles Excellent communication and interpersonal skills Preferred Skills: Experience in a startup environment (highly preferred) Knowledge of performance management systems Familiarity with HRIS and compliance regulations Pay range and compensation package: The salary range for this role (3-5 years of experience) would be approximately: ₹10–12 LPA including variable components Equal Opportunity Statement: We are committed to diversity and inclusivity in our hiring practices and strive to create a workplace where everyone feels valued and respected. If you're ready to make a lasting impact and help shape the future of AI and Data Science, Aria’s Science Lab is the place for you!
As a member of the Aria Intelligent Solutions team located in Kolkata or Delhi, India, you will have the opportunity to contribute to cutting-edge research and development in the field of Artificial Intelligence. Aria is dedicated to combining industry expertise with the latest technological advancements to achieve exceptional outcomes. By being a part of our team, you will play a crucial role in pioneering advancements in NLP (Natural Language Processing) and Generative AI, driving innovation and delivering impactful solutions. Your responsibilities will include conducting groundbreaking research in NLP and Generative AI, continuously exploring new techniques and algorithms to enhance our understanding and applications. You will be tasked with designing, implementing, and training advanced NLP and Generative AI models for various purposes such as text generation, machine translation, question answering, and sentiment analysis. Data analysis will also be a key aspect of your role, involving the cleaning, preprocessing, and analysis of extensive datasets to derive valuable insights that will guide model development. Collaboration with cross-functional teams to identify and address complex data-driven challenges will be essential. You will be expected to contribute to driving innovation by discovering new applications of NLP and Generative AI across diverse domains. Furthermore, you will have the opportunity to provide mentorship and guidance to junior data scientists and researchers, sharing your expertise and fostering their professional growth. To excel in this role, you should possess a Master's or Ph.D. degree in Computer Science, Data Science, or a related field, along with 7-8 years of experience in data science focusing on NLP and Generative AI. Proficiency in Python and common data science libraries is required, as well as a deep understanding of NLP concepts and techniques such as tokenization, stemming, lemmatization, feature engineering, and various deep learning architectures. Familiarity with state-of-the-art NLP models and frameworks like Transformers, BERT, and GPT is crucial. Strong problem-solving skills, the ability to work independently, excellent communication skills, and effective collaboration with cross-functional teams are also vital for success in this role. Bonus points will be awarded if you have experience with cloud platforms like AWS, GCP, or Azure, knowledge of machine learning operations (MLOps) and data pipelines, and a track record of publications in top-tier conferences or journals within the NLP or AI field. A passion for continuous learning and keeping abreast of the latest developments in NLP and Generative AI will further enhance your contributions to our team at Aria Intelligent Solutions.,
Python Backend Engineer Experience: 3-7 years Location: Delhi Work Mode: Hybrid We’re looking for a Python Backend Engineer who’s passionate about building robust, scalable, and high-performance backend systems. You’ll design and implement APIs, microservices, and message-driven architectures that power data-intensive and real-time applications. What You’ll Do: Design, develop, and maintain scalable backend services using Python (FastAPI / Flask / Django). Build and optimize RESTful APIs and microservices architectures. Integrate and manage message queue systems such as RabbitMQ, Kafka, or Celery for asynchronous processing. Collaborate with frontend, data, and DevOps teams to deliver reliable end-to-end solutions. Ensure performance, scalability, and security of backend systems. Write clean, modular, and well-tested code following best practices. Monitor, troubleshoot, and improve system reliability and performance. What We’re Looking For: 3–7 years of professional experience in backend development with Python. Strong experience with FastAPI, Flask, or Django REST Framework. Hands-on experience with message queues (e.g., RabbitMQ, Kafka, Celery, Redis Streams). Solid understanding of microservice architecture, asynchronous programming, and API design. Proficiency in SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, etc.). Familiarity with Docker, Kubernetes, or CI/CD pipelines. Experience working with cloud environments (AWS, GCP, or Azure). Strong debugging, optimization, and problem-solving skills. Nice to Have: Experience with event-driven architectures or real-time data pipelines. Knowledge of GraphQL, gRPC, or WebSockets. Exposure to monitoring tools (Prometheus, Grafana, ELK). Familiarity with unit testing, pytest, or integration testing frameworks. Why Join Us: Work on high-performance backend systems that handle large-scale data and messaging workloads. Collaborate with a skilled, cross-functional engineering team. Modern tech stack, agile environment, and growth opportunities. Competitive compensation, flexibility, and innovation-driven culture. If this sounds like the role for you, send your CV today!
As a Data Scientist/Senior Data Scientist – Price Optimization, Demand Modelling & Forecasting, you will play a critical role in developing and deploying advanced machine learning models for price optimization, cannibalization impact analysis, and demand forecasting. In addition to your technical expertise, you'll be a key point of contact for client management—leading client-facing projects and delivering actionable insights to address complex business problems. You will collaborate closely with cross-functional teams, translating business requirements into scalable data solutions while ensuring alignment with client objectives. You’ll also mentor and guide junior data scientists, fostering a collaborative and innovative environment to ensure continuous learning and growth. Role and Responsibilities: Model Development: Design, implement, and scale machine learning solutions for price elasticity, price and promotion optimization, cannibalization effects, and demand modelling/forecasting across FMCG and Retail sectors. Develop and validate models that quantify cross-product impacts and substitution effects to optimize overall category performance. Hands-On Data Science: Lead end-to-end model development using PySpark, Databricks, and other distributed computing environments for efficient large-scale data processing and model training. Write modular, scalable code for model development using libraries such as pulp, cvxpy, Temporal Fusion Transformers, XGBoost, and time series modelling libraries. Collaborative Problem Solving: Work closely with cross-functional teams to identify business challenges, define data-driven solutions, and implement dynamic pricing, cannibalization, and forecasting tools. Client Management: Serve as the primary data science lead for client interactions—managing expectations, providing technical expertise, and presenting actionable, data-driven insights. Ensure timely project delivery, alignment with business goals, and sustained client satisfaction. Innovation: Continuously explore and test innovative approaches in price elasticity modelling, cross-product cannibalization analysis, and demand forecasting. Drive innovation to improve existing pricing and forecasting frameworks for better commercial outcomes in the FMCG/Retail sector. Mentorship: Provide guidance and mentorship to junior data scientists, encouraging best practices in model design, coding, and documentation. Skills and Experience: Essential: Master’s or Ph.D. in Computer Science, Data Science, Statistics, Operations Research, or related field. 3–10 years of experience in data science with a focus on price optimization, demand forecasting, and cannibalization modelling, preferably in FMCG or Retail. Strong experience in PySpark for large-scale data processing and model deployment. Proven ability to develop and implement demand and price elasticity models, interpret cross-product interactions, and deliver business impact. Strong problem-solving skills and ability to translate quantitative findings into strategic recommendations. Excellent communication skills with the ability to explain complex models to non-technical stakeholders. Demonstrated experience managing client relationships and delivering results in cross-functional, fast-paced environments. Ideal: Experience with cloud platforms (AWS, GCP, Azure) for scalable model development and deployment. Familiarity with MLOps and automated deployment pipelines for pricing and forecasting models. Published work or contributions in areas such as pricing optimization, demand modelling, or retail analytics in reputed journals or conferences.
Role Overview: As a Data Scientist/Senior Data Scientist specializing in Price Optimization, Demand Modelling & Forecasting, you will be instrumental in creating and implementing advanced machine learning models for optimizing prices, analyzing cannibalization impact, and forecasting demand. Beyond your technical proficiency, your role will involve managing client relationships, leading client-facing projects, and providing actionable insights to tackle complex business challenges. Collaboration with cross-functional teams to develop scalable data solutions aligned with client objectives and mentoring junior data scientists to foster a culture of continuous learning and innovation will be key aspects of your responsibilities. Key Responsibilities: - Design, implement, and scale machine learning solutions for various areas including price elasticity, price and promotion optimization, cannibalization effects, and demand modelling/forecasting in the FMCG and Retail sectors. - Lead end-to-end model development utilizing PySpark, Databricks, and other distributed computing environments for efficient large-scale data processing and model training. - Work collaboratively with cross-functional teams to identify business challenges, define data-driven solutions, and implement dynamic pricing, cannibalization, and forecasting tools. - Serve as the primary data science lead for client interactions, managing expectations, providing technical expertise, and presenting actionable, data-driven insights. - Continuously explore and test innovative approaches in price elasticity modelling, cross-product cannibalization analysis, and demand forecasting to drive improvements in pricing and forecasting frameworks. - Provide guidance and mentorship to junior data scientists to encourage best practices in model design, coding, and documentation. Qualifications Required: - Masters or Ph.D. in Computer Science, Data Science, Statistics, Operations Research, or a related field. - 3-10 years of experience in data science with a focus on price optimization, demand forecasting, and cannibalization modelling, preferably in FMCG or Retail industries. - Strong experience in PySpark for large-scale data processing and model deployment. - Proven ability to develop and implement demand and price elasticity models, interpret cross-product interactions, and deliver business impact. - Strong problem-solving skills and the ability to translate quantitative findings into strategic recommendations. - Excellent communication skills with the ability to explain complex models to non-technical stakeholders. - Demonstrated experience in managing client relationships and delivering results in cross-functional, fast-paced environments. Additional Company Details (if available): No additional company details are provided in the job description.,
We’re looking for a UI/UX Designer who can turn complex ideas into simple, delightful user experiences. You’ll work closely with product managers, developers, and stakeholders to design intuitive, beautiful, and functional digital products that users love. What You’ll Do Create user-centered designs by understanding business requirements, user feedback, and behaviour. Develop wireframes, prototypes, and high-fidelity designs using Figma , Adobe XD , or Sketch . Collaborate with product and engineering teams to translate design concepts into seamless user experiences. Conduct user research , usability testing , and journey mapping to inform design decisions. Define and maintain design systems , ensuring consistency across platforms and features. Stay updated with modern design trends, accessibility guidelines, and UX best practices. What We’re Looking For 3–10 years of experience as a UI/UX Designer or Product Designer . Strong portfolio demonstrating UI design, UX process, and problem-solving ability. Proficiency in design tools like Figma , Adobe XD , Sketch , Illustrator , or Photoshop . Solid understanding of responsive design , interaction design , and design systems . Familiarity with frontend frameworks (React, HTML/CSS) is a plus. Excellent communication and collaboration skills — you can explain your design choices clearly. Bonus Points Experience working on AI-driven , SaaS , or data-heavy applications . Knowledge of motion design or micro-interactions . Understanding of WCAG accessibility and user psychology principles. Why Join Us Shape user experiences that power next-generation products. Work in a creative, fast-paced, and growth-oriented environment. Collaborate with cross-functional teams passionate about design and innovation. Competitive pay, flexibility, and opportunities for continuous learning
As a Data Scientist/Senior Data Scientist – Price Optimization, Demand Modelling & Forecasting, you will play a critical role in developing and deploying advanced machine learning models for price optimization, cannibalization impact analysis, and demand forecasting. In addition to your technical expertise, you'll be a key point of contact for client management—leading client-facing projects and delivering actionable insights to address complex business problems. You will collaborate closely with cross-functional teams, translating business requirements into scalable data solutions while ensuring alignment with client objectives. You’ll also mentor and guide junior data scientists, fostering a collaborative and innovative environment to ensure continuous learning and growth. Role and Responsibilities: Model Development: Design, implement, and scale machine learning solutions for price elasticity, price and promotion optimization, cannibalization effects, and demand modelling/forecasting across FMCG and Retail sectors. Develop and validate models that quantify cross-product impacts and substitution effects to optimize overall category performance. Hands-On Data Science: Lead end-to-end model development using PySpark, Databricks, and other distributed computing environments for efficient large-scale data processing and model training. Write modular, scalable code for model development using libraries such as pulp, cvxpy, Temporal Fusion Transformers, XGBoost, and time series modelling libraries. Collaborative Problem Solving: Work closely with cross-functional teams to identify business challenges, define data-driven solutions, and implement dynamic pricing, cannibalization, and forecasting tools. Client Management: Serve as the primary data science lead for client interactions—managing expectations, providing technical expertise, and presenting actionable, data-driven insights. Ensure timely project delivery, alignment with business goals, and sustained client satisfaction. Innovation: Continuously explore and test innovative approaches in price elasticity modelling, cross-product cannibalization analysis, and demand forecasting. Drive innovation to improve existing pricing and forecasting frameworks for better commercial outcomes in the FMCG/Retail sector. Mentorship: Provide guidance and mentorship to junior data scientists, encouraging best practices in model design, coding, and documentation. Skills and Experience: Essential: Master’s or Ph.D. in Computer Science, Data Science, Statistics, Operations Research, or related field. 3–10 years of experience in data science with a focus on price optimization, demand forecasting, and cannibalization modelling, preferably in FMCG or Retail. Strong experience in PySpark for large-scale data processing and model deployment. Proven ability to develop and implement demand and price elasticity models, interpret cross-product interactions, and deliver business impact. Strong problem-solving skills and ability to translate quantitative findings into strategic recommendations. Excellent communication skills with the ability to explain complex models to non-technical stakeholders. Demonstrated experience managing client relationships and delivering results in cross-functional, fast-paced environments. Ideal: Experience with cloud platforms (AWS, GCP, Azure) for scalable model development and deployment. Familiarity with MLOps and automated deployment pipelines for pricing and forecasting models. Published work or contributions in areas such as pricing optimization, demand modelling, or retail analytics in reputed journals or conferences.
Job Title: Data Scientist/Senior Data Scientist – Forecasting Location: Delhi & Kolkata (Hybrid) Experience: 3–10 years Employment Type: Full-time About Us Aria Intelligent Solutions, is a cutting-edge AI company that specializes in building scalable AI solutions to its clients in various domains, starting from Retail, Pharmaceuticals to FMCG. We’re a fast-growing, innovation-driven team committed to solving real-world problems through cutting-edge AI and machine learning technologies. Role Overview We are looking for a Data Scientist/Senior Data Scientist with strong expertise in forecasting and time-series modeling to lead the design, development, and deployment of predictive solutions. The ideal candidate will work closely with product, engineering, and business teams to translate complex data into actionable insights and robust forecasting systems. Key Responsibilities Design, develop, and deploy forecasting and time-series models for business and product use cases Apply statistical and machine learning techniques such as ARIMA/SARIMA, Prophet, state-space models, XGBoost, LSTM, and ensemble methods Analyze historical data to identify trends, seasonality, anomalies, and external drivers Collaborate with product managers and stakeholders to define forecasting requirements and success metrics Build scalable data pipelines and model workflows for production environments Evaluate and improve model performance using appropriate error metrics (MAPE, RMSE, MAE, etc.) Communicate insights and forecasts clearly through dashboards, reports, and presentations Mentor junior data scientists and contribute to best practices across the data science team Required Skills & Qualifications 3+ years of hands-on experience in data science with a strong focus on forecasting Strong foundation in statistics, probability, and time-series analysis Proficiency in Python (NumPy, Pandas, Scikit-learn, Statsmodels) Experience with forecasting libraries such as Prophet, pmdarima, darts, or equivalent Experience working with SQL and large datasets Understanding of model deployment, monitoring, and retraining in production Ability to translate business problems into analytical solutions Good to Have Experience with deep learning models for time-series (LSTM, GRU, Temporal CNNs) Exposure to cloud platforms (AWS, Azure, GCP) and MLOps tools Experience in domains like retail, supply chain, finance, demand forecasting, or market intelligence Knowledge of data visualization tools (Power BI, Tableau, or similar) Why Join Us Work on impactful AI products with real-world applications Collaborative, innovation-driven culture Opportunity to influence product direction and architecture Competitive compensation and growth opportunities