About Gameskraft
Established in 2017, Gameskraft has become one of India’s fastest-growing companies. We are building the world's most-loved online gaming ecosystem, one game at a time. Started by a group of passionate gamers, we have grown from a small team of 5-6 members to a large family of 600+ Krafters, working out of our office in Prestige Tech Park, Bangalore.
Our short-term success lies in the fact that we strive to focus on building a safe, secure, and responsible gaming environment for everyone. Our vision is to create unmatched experiences every day and everywhere. We set the highest benchmarks in the industry in terms of design, technology, and intuitiveness. We are the industry’s only ISO 27001 and ISO 9001 certified company.
Lead Data Scientist
As Lead Data Scientist, you'll be actively involved in the daily development and execution of advanced analytics and machine learning solutions. You'll shape the data strategy, lead the team in deriving insights from large datasets, and ensure the successful deployment of data-driven solutions to achieve business goals.
You will have the opportunity to collaborate on a diverse range of projects across multiple business units, gaining exposure to different aspects of the organization. This will allow you to broaden your expertise, learn from various domains, and understand how data science can drive value in different areas. Working on these varied projects will help you develop a well-rounded skill set, enabling you to tackle complex challenges and apply data-driven solutions in different contexts.
As a Lead Data Scientist, you will :
Data Strategy:
Develop and execute a comprehensive data strategy that aligns with the organization's objectives.
Identify, prioritize, and drive data science opportunities that maximize business value.
Advocate for data-driven decision-making across the organization.
Advanced Analytics and Machine Learning:
Lead the design, development, and deployment of advanced analytics and machine learning models.
Ensure the team leverages state-of-the-art techniques, tools, and frameworks to address complex business challenges.
Drive experimentation, hypothesis testing, and model validation to optimize outcomes.
Data Governance and Quality:
Establish and enforce best practices for data governance, security, and compliance.
Work closely with data engineering teams to maintain high-quality, reliable, and well-documented data pipelines.
Ensure scalability, reproducibility, and transparency of data science workflows.
Collaboration:
Partner with business stakeholders to understand key objectives and translate them into actionable data science initiatives.
Work with different functions like product, business, marketing, and engineering teams to integrate data science solutions into production systems.
Act as a bridge between technical teams and business leaders, ensuring alignment and impact.
Innovation and Thought Leadership:
Stay ahead of industry trends, emerging technologies, and best practices while fostering a culture of continuous learning, experimentation, and knowledge-sharing.
Drive innovation by exploring novel methodologies, publishing research in reputed AI and data science conferences, and contributing to intellectual property through patents.
Share thought leadership through blogs, whitepapers, and industry forums to influence and advance the field.
Performance Measurement and Impact Assessment:
Define and monitor key performance indicators (KPIs) to measure the success of data science initiatives.
Continuously assess and refine models, tools, and processes to enhance business impact.
Promote a results-driven mindset, ensuring data science contributes to measurable business outcomes.
Communication and Stakeholder Engagement:
Effectively translate complex technical concepts into clear, actionable insights for non-technical audiences.
Prepare and deliver reports, presentations, and thought leadership materials for senior management and other stakeholders.
Advocate for data science across the organization, influencing decision-makers to embrace data-driven strategies.
Mentorship and Team Development
Lead, mentor, and inspire the data science team to excel in technical and strategic problem-solving.
Provide technical guidance, best practices, and hands-on support in model development and deployment.
Foster an environment of continuous learning, encouraging skill enhancement through training, workshops, and knowledge-sharing sessions.
What we expect you will bring to the table :
A Master's or Ph.D. in Computer Science, Statistics, Machine Learning, or a related field.
5-8 years of hands-on experience in delivering production-ready data science projects.
Strong expertise in machine learning, statistical modeling, and data analytics, with hands-on experience in algorithms such as regression, classification, clustering, and time series analysis. Deep Learning and GenAI Experience is a plus.
Proficient programming skills in languages like Python, with experience in libraries such as scikit-learn, TensorFlow, Keras, PyTorch, Pandas, NumPy, and Matplotlib for data manipulation, modeling, and visualization.
Experience with big data technologies such as Hadoop, Spark, and distributed computing frameworks for processing large datasets.
Familiarity with cloud platforms like AWS, Azure, or Google Cloud, including services like S3, Redshift, Databricks, and Machine Learning platforms.
Experience publishing research papers at reputed AI conferences is a plus.
Proven success in implementing data science solutions that generate business value.
Strong communication and leadership abilities.
Familiarity with industry-specific regulations and data compliance standards.
If you are passionate about creating exceptional user experiences, possess strong leadership skills, and have a track record of delivering successful data science, we encourage you to apply for this exciting opportunity.
We are committed to providing equal opportunity in employment and creating an inclusive work environment.
Remember, together, we can achieve more!
