Senior Forecasting Analyst

Were Hiring: Senior Associate Forecasting at Chryselys Location: Hyderabad About Us: Chryselys is a Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations. We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights. Who we are: People - Our team of industry veterans, advisors and senior strategists have diverse backgrounds and have worked at top tier companies. Quality - Our goal is to deliver the value of a big five consulting company without the big five cost. Technology - Our solutions are Business centric built on cloud native technologies. Role Overview: We are seeking a highly motivated and analytical Pharma Commercial Forecasting Senior Associate to join our growing team. In this role, you will develop accurate and insightful forecasts to support strategic decision-making across the product lifecycle. You will leverage your expertise in market research, data analysis, and forecasting methodologies to assess market opportunities, develop long-term plans, and identify potential risks. Key Responsibilities: - Market and Opportunity Assessments: Conduct Robust market and opportunity assessments to identify growth opportunities and market trends for product launches, portfolio management, and business development strategies. - Forecasting Models: Develop and maintain robust forecasting models using methodologies such as time series analysis, analogy forecasting, and market sizing techniques. Experience with Python and SQL is a plus. - Data Analysis: Utilize industry-standard databases (e.G., IQVIA) and internal data sources to analyse market trends, competitor activity, and customer behaviour. - Sales Forecasts: Create accurate short-term and long-term sales forecasts to support budgeting, resource allocation, and operational planning, using a combination of qualitative and quantitative data. - Scenario Planning: Participate in scenario planning and risk assessment exercises to identify potential roadblocks and develop mitigation strategies. - Cross-Functional Collaboration: Collaborate with cross-functional teams to align forecasting models with business goals. - Communication: Effectively communicate forecasting results through presentations and reports tailored to different stakeholder audiences. - Process Improvement: Continuously monitor and improve forecasting methodologies and processes. Enhance and streamline routine processes through standardization and automation to increase efficiency and flexibility. - Research Support: Provide support with secondary research and analysis; stay informed on the latest therapeutic research, clinical developments, and competitive landscape to inform forecasting activities. What You Bring: Experience: 2+ years of experience in the pharmaceutical or life science industry. Skills: - Good understanding of pharma/oncology disease areas and indications. - Strong technical skills and functional expertise in inline & pipeline forecasting with specialized skills in creating models using epi and trend-based approaches. - Ability to collaborate with internal and external stakeholders for diverse forecasting needs: Strategic/long range planning, budget/tactical planning, Sales & Ops. Planning, Business Development & Licensing etc. - Strong analytical skills with experience in data analysis, manipulation, coding and visualization (experience with Python, Excel/VBA, Qlik/Tableau and SQL preferred). - Good understanding of quintessential US, RE and Global pharma datasets for sales/Rx & EPI. - Experience with market research techniques and familiarity with market research tools and databases. - Ability to independently work and deliver projects across brand life cycle. - Passion and commitment to achieve results through individual excellence and collaboration. - Strong problem solving, communication and customer orientation. - Understanding of industry standard forecasting platforms, tools and technologies is a plus. Preferred Qualifications: Educational Qualifications: Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Engineering or a related field.